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The Journal of Immunology, 2007, 178: 3134-3142.
Copyright © 2007 by The American Association of Immunologists, Inc.

Differential Recognition of TLR-Dependent Microbial Ligands in Human Bronchial Epithelial Cells1

Anja K. Mayer*, Mario Muehmer*, Jörg Mages{dagger}, Katja Gueinzius{ddagger}, Christian Hess§, Klaus Heeg*, Robert Bals§, Roland Lang{dagger} and Alexander H. Dalpke2,*

* Department of Medical Microbiology and Hygiene, University Heidelberg, Heidelberg, Germany; {dagger} Institute of Medical Microbiology, Immunology and Hygiene, Technische Universität München, Munich, Germany; {ddagger} Biochemical Pharmacology, University of Konstanz, Konstanz, Germany; and § Department of Internal Medicine, Division for Pulmonary Diseases, Philipps-University Marburg, Marburg, Germany


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
Bronchial epithelial cells represent the first line of defense against invading airborne pathogens. They are important contributors to innate mucosal immunity and provide a variety of antimicrobial effectors. However, mucosal surfaces are prone to contact with pathogenic, as well as nonpathogenic microbes, and therefore, immune recognition principles have to be tightly controlled to avoid uncontrolled permanent activation. TLRs have been shown to recognize conserved microbial patterns and to mediate inducible activation of innate immunity. Our experiments demonstrate that bronchial epithelial cells express functional TLR1–6 and TLR9 and thus make use of a common principle of professional innate immune cells. Although it was observed that TLR2 ligands dependent on heterodimeric signaling either with TLR1 or TLR6 were functional, other ligands like lipoteichoic acid were not. Additionally, it was found that bronchial epithelial cells could be stimulated only marginally by Gram-positive bacteria bearing known TLR2 ligands while Gram-negative bacteria were easily recognized. This correlated with low expression of TLR2 and the missing expression of the coreceptor CD36. Transgenic expression of both receptors restored responsiveness to the complete set of TLR2 ligands and Staphylococcus aureus. Additional gene-array experiments confirmed hyporesponsiveness to this bacterium while Pseudomonas aeruginosa and respiratory syncytial virus induced common, as well as pathogen-specific, sets of genes. The findings indicate that bronchial epithelium regulates its sensitivity to recognize microbes by managing receptor expression levels. This could serve the special needs of controlled microbial recognition in mucosal compartments.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
Pathogen entry via the mucosal route is the most common way infections occur and the lung possesses the largest epithelial surface in the body. The upper airways are exposed to inhaled airborne pathogens, and because of this, bronchial epithelial cells are equipped with several different means of defense against invading pathogens (1). Bronchial epithelial cells build up a tight physical barrier and are embedded in a mucus layer that hinders pathogens from penetrating the body. Another method of defense used by bronchial epithelial cells is their ability to use mucociliary clearance to entrap and remove microorganisms. The bronchial epithelium also produces antimicrobial substances, including lysozyme, lactoferrin, collectins, and antimicrobial peptides, which provide a further protective cover. Despite these functions, which are always active, it has been proposed recently that epithelial cells also are able to sense microbes, which leads to the inducible secretion of further mediators, including chemokines to orchestrate a local inflammatory response (2). To accomplish this, bronchial epithelium specifically makes use of TLRs that recognize conserved microbial structures (3). Bronchial epithelial cells have also been described to functionally express TLR1–6 and TLR9 (4, 5, 6, 7).

It is now evident that TLRs react to conserved microbial structures from both pathogenic and nonpathogenic microbes (8). Although this does not play a role for the recognition of microbes in blood monocytes or tissue macrophages that are embedded in sterile compartments, it does represent a problem for mucosal surfaces, which are regularly exposed to microbes. Thus, specific mechanisms must exist in epithelial cells to not only assure appropriate recognition of invading pathogens but also to avoid being continuously activated. Different observations support this view: in intestinal epithelium, it has been demonstrated that TLR4 is expressed mainly intracellularly (9), and TLR5 seems to be restricted to the basolateral membrane (10). As a consequence, recognition of luminal commensal bacteria is avoided. TLR sensitivity is lost shortly after birth due to down-regulation of crucial signaling molecules (11). Similarly, it has been proposed that, in bronchial epithelium, TLR4 is expressed intracellularly (12); however, TLR2 can also be found on the surface (13, 14). It was also observed that the level of receptor expression regulates the sensitivity to TLR ligands, which is of importance in the gut (15, 16). Finally, coreceptors play an increasingly important role in TLR signaling. To this end, CD14, LPS-binding protein, and additional proteins are involved in TLR4 signal transduction (17, 18), and CD36 has been shown to mediate sensitivity to TLR2-dependent diacylglycerides and lipoteichoic acid (LTA)3 (19).

The task of mounting an appropriate response to invading pathogens means that different microbes have to be attacked by specific effectors. It is known that pathogens in the lung show some specificity for different TLRs, e.g., RNA viruses can activate TLR3 (20, 21) and Gram-positive bacteria via lipopeptides are activators of TLR2 (13) while LPS from Enterobacteriaceae potently stimulates TLR4 (12). Genome-wide studies in macrophages and dendritic cells have indicated that common, as well as specific, inflammatory programs in response to different TLR ligands or whole microbes exist (22, 23). These findings support a concept of pathogen-adopted responses not only in adaptive but also in innate immunity.

In this article, we addressed the question of TLR-mediated responses and pathogen-specific recognition in bronchial epithelium.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Disclosures
 References
 
Reagents

RPMI 1640 and DMEM were purchased from Biochrom. FCS was from Biowest. Ham’s F12:DMEM (1:1) and LipofectAMINE 2000 were purchased from Invitrogen Life Technologies. Ultroser G was received from Ciphergen. LTA from Staphylococcus aureus was purified as described (24). MurNAc-L-ala-{gamma}-D-Glu-meso-diaminopimelic acid (DAP) and muramyl dipeptide (MDP) were a gift from C. Hermann (Biochemical Pharmacology, University of Konstanz, Konstanz, Germany). LPS from Salmonella minnesota was provided by U. Seydel (Division of Biophysics, Research Center Borstel, Borstel, Germany). Poly(deoxyinosinic-deoxycytidylic acid) (pI:C) and mannan from Saccharomyces cerevisiae were purchased from Sigma-Aldrich. Pam3CysSK4 (P3C), Pam2CysSK4 (P2C), R-FSL-1, and S-FSL-1, which are analogs of mycoplasma-derived macrophage activating linopeptide-2 (25), were obtained from EMC Microcollections. Phosphorothioate-modified CpG-ODN 2006 (TCG TCG TTT TGT CGT TTT GTC GTT) was custom synthesized by TIB Molbiol. Recombinant IL-1beta was purchased from Tebu.

Bacteria and viruses

Respiratory syncytial virus (RSV) strain A2 was a gift from S. Ehl (Children’s Hospital, University of Freiburg, Freiburg, Germany). The following bacterial strains were used: Escherichia coli (ATCC 25922), Klebsiella pneumoniae (ATCC 700603), Legionella pneumophila (corby strain; K. Heuner, Institute for Molecular Infection Biology, University of Würzburg, Würzburg, Germany), Haemophilus influenzae (ATCC 49247), Pseudomonas aeruginosa (ATCC 27853), S. aureus (ATCC 29213), Staphylococcus epidermidis (ATCC 12228), Streptococcus pneumoniae (patient isolate), Streptococcus oralis (ATCC 35037), Streptococcus agalactiae (ATCC 27956), and Listeria monocytogenes (patient isolate).

Cell culture and determination of cytokine secretion

Human bronchial epithelial cell lines BEAS-2B, IHAEo–, 16-HBE, MM-39, and primary respiratory epithelial cells isolated from large airways and cultivated in air-liquid interface cultures were maintained as described previously (6). Twenty-four hours before stimulation, 2.5 x 104 cells were seeded in 96-well plates in 200 µl of medium in duplicate and treated as described in the experiment. Cell-free supernatants were harvested and analyzed for cytokines by commercially available ELISA kits (BD Biosciences).

Cloning of human CD36

Human CD36 was cloned from cDNA by PCR into pcDNA3.1D/V5-His-TOPO vector (Invitrogen Life Technologies). Plasmid identity was controlled by automated sequencing. Expression of CD36 was controlled by flow cytometry and Western blotting.

Epithelial cell transfection

BEAS-2B epithelial cells were seeded at 2 x 104/well in 96-well plates 24 h before transfection. Cells were transfected using LipofectAMINE 2000 according to the manufacturer’s instructions. Each sample contained 600 ng of control vector or 300 ng of human TLR2 and human CD36, respectively. Six hours posttransfection medium was exchanged to normal growth medium. At 24 h posttransfection, cells were stimulated overnight at 37°C. Cell-free supernatants were harvested and analyzed for IL-8 by ELISA (BD Biosciences).

Flow cytometry analysis

Twenty-four hours before transfection epithelial cells were seeded at 3.5 x 105/well in 6-well plates. Cells were transfected with 4 µg of CD36 or TLR2 expression plasmid (the latter was obtained from T. Espevik, Norwegian University of Science and Technology, Trondheim, Norway). Magnetically sorted CD14+ monocytes (MACS; Miltenyi Biotec) were used as a positive control. Twenty-four hours posttransfection, cells were stained with PE-anti-CD36 (BD Biosciences) or FITC-anti-TLR2 (eBioscience) and analyzed on a FACSCanto flow cytometer (BD Biosciences).

Quantitative RT-PCR

Total RNA from 2 x 105 cells was isolated using HighPure RNA kit (Roche), which included DNase I digestion. Total RNA (1 µg) was reverse transcribed with a cDNA synthesis kit (MBI Fermentas). cDNA, diluted 1/5, was used as template in the quantitative PCR mix according to the manufacturer’s standard protocol (Absolute SYBR Green Rox Mix; Abgene). PCR was performed on a 7900HAT platform (Applied Biosystems). Primer sequences are available on request. Specificity of RT-PCR was controlled by no-template and no-reverse transcription controls and melting curve analysis. If not indicated otherwise, results are expressed relative to the expression of the housekeeping gene beta-actin (1/2{Delta}Ct).

Western blot analysis

A total of 3.5 x 105 cells was transfected with 4 µg of a CD36 expression plasmid. After 24 h, cells were lysed according to standard procedures and cleared amounts of lysates were fractionated by 12% SDS-PAGE and electrotransferred to polyvinylidene difluoride membranes. Membranes were stained with anti-His-Ab (Qiagen), and detection was done by ECL (PerkinElmer).

Murine bone marrow cell stimulation

TLR2 knockout mice were provided by Tularik (South San Francisco, CA). Bone marrow cells were isolated from both femurs by rinsing with 10 ml of ice-cold PBS. After centrifugation, cells were resuspended in RPMI 1640 containing 10% FCS and transferred to 96-well cell-culture plates (5 x 106 cells/well). Cells were then incubated with different stimuli for 24 h, and cell-free supernatants were examined for cytokine production by ELISA.

Gene expression profiling

Twenty-four hours before stimulation 1 x 106 cells were seeded in 6-well plates. Cells were stimulated in triplicates with 108/ml UV-inactivated P. aeruginosa or S. aureus or with RSV (multiplicity of infection (MOI) 1) for 4 h. RNA was isolated using HighPure RNA kit (Roche). RNA quality was checked on a Bio-Rad Experion automated electrophoresis system (Bio-Rad). Total RNA (3 µg) was processed and hybridized to the human expression array U133A 2.0 according to the manufacturer’s protocols (Affymetrix). Microarrays were scanned and initially analyzed using Affymetrix GCOS software. Each array was checked for general assay quality (mean average background noise of 69 with a SD of 19, scaling factors ranging between 0.3 and 0.6 and 3'-5' ratios for GAPDH and beta-actin < 1.1). CEL files were processed for global normalization, and expression values were generated using the robust multiarray analysis algorithm in the R affy package (www.bioconductor.org) (26). The data discussed in this publication have been deposited in NCBIs Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession GSE6802.

The list of significantly regulated genes was achieved by applying the Significance Analysis of Microarrays multiclass algorithm (27) of the samr package for R over all four conditions used in the setup (medium, S. aureus, RSV, and P. aeruginosa). The one percent false discovery rate level for differentially regulated genes exceeded 1364 probe sets. Further filtering on a max (all averages)/min (all averages) > 2 resulted in 701 probe sets. For evaluation purposes if the change in the mean expression values between individual conditions is significantly different at a 5% confidence level, a Tukey-Honest Significant Differences Test was superimposed. Further filtering and data preparation was performed with the Spotfire DescionSite software (Spotfire Sommerville). A heat map was generated using the program Genesis (release 1.6.0) (28). Analysis of overrepresentation of GO terms was done with Genomatix Bibliosphere (www.genomatix.de).


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Disclosures
 References
 
Human bronchial epithelial cells functionally express TLRs

We first analyzed the expression of various pattern recognition receptors by RT-PCR in four different human bronchial epithelial cell lines (BEAS-2B, IHAEo–, 16-HBE, and MM-39) and in primary airway epithelial cells in submersed and in air-liquid interface cultures. TLR1, TLR3, TLR4, and TLR6 were detected in all cells and TLR2 and TLR5 were expressed in five of six cells (data not shown). TLR7 and TLR8 were not expressed in any epithelial cells, but low TLR9 expression could be detected in primary epithelium. In addition, we detected transcripts for NOD1, mannose receptor, CD14, and high-affinity N-fMLP receptor. In contrast, no expression was found for NOD2, the four human peptidoglycan recognition proteins and dectin-1. To assure the functional expression of the detected receptors we stimulated BEAS-2B cells with highly purified specific ligands (Fig. 1, a and b). Ligands for TLR1 (P3C), –2 (P3C, LTA, R-FSL), –3 (pI:C), –4 (LPS), –6 (R-FSL), –9 (CpG), and NOD1 (DAP) were able to induce IL-8 and IL-6 secretion with different efficacy. No activation of TLR7 and TLR8 by R848 was observed, which is consistent with the missing expression of both receptors. Additionally, the mannose receptor, although weakly expressed, could not be activated by use of mannan (man) and NOD2 stimulation by MDP was not possible. A quite similar response pattern was observed with primary epithelial cells. However, primary cells showed a much weaker response to LPS as compared with BEAS-2B cells (Fig. 1c).


Figure 1
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  		FIGURE 1. Differential recognition of microbial patterns in human bronchial epithelium. a and b, BEAS-2B cells were stimulated with purified ligands for different pattern recognition receptors overnight. Concentrations were 10 µg/ml P3C, LTA, mannose, 5 µg/ml DAP, MDP, 1 µg/ml R-FSL-1, pI:C, R848, 1 µM CpG, and 10 ng/ml LPS, IL-1beta. IL-8 (a) and IL-6 (b) secretion was measured in the supernatant (mean of triplicates + SD, one typical of four experiments). c, Primary bronchial epithelial cells were stimulated as above. IL-8 was determined by ELISA and set in reference to unstimulated control cells (fold induction) (n = 2, mean + SD). d and e, Cells were stimulated with lipoteichoic acids from S. aureus (LTA Sa), S. pneumoniae (LTA Sp), L. monocytogenes (LTA L), LPS from Porphyromonas gingivalis (LPS Pg) (each 10 µg/ml), P2C, P3C (5 µg/ml), R-FSL-1 or S-FSL-1 (1 µg/ml), and IL-8 secretion (d) (overnight stimulation, mean + SD of two independent experiments) and mRNA induction (e) (2 h stimulation, mean + SD of two independent experiments) were determined. f, Stimuli from above were applied to murine bone marrow cells from TLR2–/– or wild-type mice and analyzed for TNF secretion (mean + SD, n = 3).

 
Ligand-dependent differences in TLR2 activation

Surprisingly, we observed that BEAS-2B cells behaved differently to the TLR2 ligands P3C and R-FSL-1 as compared with LTA with LTA being inactive. To examine this in more detail, we used additional stimuli for TLR2. Only P2C, P3C, and R-FSL-1 induced significant amounts of IL-8, whereas LTA preparations of three different Gram-positive bacteria, S-FSL-1, and LPS prepared from Porphyromonas gingivalis were not able to stimulate BEAS-2B cells both at the protein and the mRNA level (Fig. 1, d and e). However, all of the compounds were shown to stimulate murine bone marrow cells in a TLR2-dependent manner (Fig. 1f) and, even more, LTA proved to be of stronger activity than the tested lipopeptides in these cells. Finally, we asked whether LTA, which itself did not stimulate BEAS-2B cells, would influence the activation by P3C. We observed that addition of LTA did not have synergistic effects but did slightly inhibit the secretion of IL-8 induced by P3C (control, 599 ± 24 pg/ml; LTA, 504 ± 6 pg/ml; P3C, 1435 ± 182 pg/ml; and LTA plus P3C, 1029 ± 37 pg/ml). Similar results were obtained for another TLR2-dependent ligand, zymosan, which also did not activate BEAS-2B cells and eliminated P3C recognition (data not shown).

Low responsiveness of bronchial epithelium cells to Gram-positive bacteria

Lipopeptides have been reported to represent major pathogen-associated molecular patterns of Gram-positive bacteria whereas typical LPS in general is a major determinant of many Gram-negative bacteria. Thus, we asked whether the differences in TLR2 responsiveness are reflected when activating epithelial cells with whole bacteria. We observed that all of the tested Gram-negative bacteria induced IL-8 in BEAS-2B cells in a dose-dependent manner whereas the Gram-positive bacteria (clinical isolates and ATCC strains) were nearly inactive (Fig. 2a). In contrast, purified CD14+ monocytes could be activated by all bacteria to secrete TNF-{alpha} albeit with different efficacy (Fig. 2b). Again, primary epithelial cells also secreted much less IL-8 in response to S. aureus or S. pneumoniae than compared with Gram-negative bacteria (Fig. 2c). To ensure that the missing responsiveness of BEAS-2B cells to Gram-positive bacteria was not due to elimination of immunostimulatory principles in the UV-inactivated bacteria, we also analyzed viable bacteria as well as bacteria inactivated by different methods. Therefore, we determined the induction of IL-8 mRNA during short-term stimulation for 2 h. Although E. coli induced IL-8 in BEAS-2B cells, S. aureus in neither of the tested preparations (viable with or without antibiotics, heat-inactivated, UV inactivated) was able to significantly induce this chemokine (Fig. 2d). Similar results were obtained for CXCL2 and CXCL3 (data not shown). However, neither LTA nor S. aureus completely lacked stimulatory activity. Increasing the stimulation period to 48 h showed that LTA and S. aureus were able to induce secretion of IL-8 (Fig. 2e), yet the amounts of IL-8 were again much lower than with P3C or IL-1beta.


Figure 2
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  		FIGURE 2. Hyporesponsiveness of BEAS-2B cells to Gram-positive bacteria. a, BEAS-2B cells were stimulated with UV-inactivated bacteria as indicated overnight. IL-8 was determined by ELISA and set in reference to unstimulated control cells (fold induction). Shown are mean values + SD of at least three independent experiments. b, CD14+ monocytes were stimulated as indicated overnight and TNF-{alpha} secretion was determined by ELISA (one of two experiments is shown). c, Primary epithelial cells were stimulated and analyzed as in a (n = 3). d, BEAS-2B cells were stimulated for 2 h with either viable E. coli or S. aureus without or in the presence of antibiotics (P/S) or with bacteria inactivated by heat treatment (70°C, 30 min) or UV treatment. Subsequently, IL-8 induction was determined by quantitative RT-PCR (mean + SD, n = 2). e, BEAS-2B cells were stimulated with UV-inactivated S. aureus (MOI 100), LTA, P3C, or IL-1beta for 48 h. IL-8 was measured in the supernatant (one of two experiments).

 
Expression levels of TLR2 and coreceptors regulate sensitivity to various TLR2 ligands

To examine the differences observed for the activation by TLR2 ligands in bronchial epithelial cells, which also went along with hyporesponsiveness to whole Gram-positive bacteria, we resorted to a quantitative measurement of TLR1–6 receptor expression (Fig. 3a). For comparison, we examined CD14+ monocytes. The latter cells expressed TLR2 slightly stronger than the other TLRs and lacked TLR3 and thus behaved essentially as predicted (29). In contrast, BEAS-2B cells expressed only low transcript numbers of TLR2 as compared with TLR1 and TLR6. TLR3 and TLR4 were most prominently expressed. Accordingly, TLR2 protein expression in BEAS-2B cells was also low in comparison to monocytes (Fig. 3b). It has been reported that CD36 is an essential coreceptor involved in the recognition of LTA and certain diacylglycerides activating TLR2/6. Using flow cytometry and quantitative RT-PCR we were not able to observe expression of CD36 in BEAS-2B cells (Fig. 3, a and b). Also, Tollip, a negative regulatory protein of TLR signaling, was not induced specifically by the nonactive TLR2 ligands (data not shown) as has been proposed for epithelial cells in the intestine (16). To analyze the meaning of missing CD36 expression and low TLR2 expression for the differing sensitivity of bronchial epithelial cells to various TLR2 ligands, we transfected BEAS-2B cells with TLR2 and CD36 expression plasmids in different combinations (Fig. 3, b and c). Transfection of CD36 alone did not result in sensitivity to LTA. Increasing the expression of TLR2 induced responsiveness to LTA in terms of IL-8 secretion. Moreover, transfection of TLR2 combined with CD36 had a synergistic effect. In contrast, none of the transfection procedures increased sensitivity to LPS or IL-1 stimulation, which is independent of TLR2 and CD36. P3C was weakly active in nontransfected cells as observed throughout this study. However, the sensitivity was also dramatically increased by TLR2 transfection. This shows that although low TLR2 expression levels are sufficient for recognition of some (P3C, P2C) TLR2 ligands BEAS-2B cells in general are hyporesponsive to TLR2-dependent microbial patterns. In the same way, responsiveness to the Gram-positive bacterium S. aureus could be induced by transfection of TLR2 and TLR2/CD36, thus paralleling the findings with LTA. Moreover, it has been reported that TNF-{alpha} and IFN-{gamma} increase expression of TLR2 in respiratory epithelial cells (30). Indeed, we observed that prestimulation of BEAS-2B cells with a combination of these both cytokines increased TLR2 mRNA expression (Fig. 3d). This translated weakly into increased expression of TLR2 at the protein level, yet CD36 was not induced (data not shown). In agreement with our other observations, we found increased IL-8 secretion of prestimulated cells in response to P3C and S. aureus but not to LTA (Fig. 3e).


Figure 3
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  		FIGURE 3. Expression levels of TLR2 and CD36 regulate sensitivity to different TLR2 ligands. a, CD14+-sorted monocytes and BEAS-2B cells were examined by quantitative RT-PCR for the expression of the indicated molecules. Transcript expression was normalized to housekeeping gene beta-actin (mean + SD, n = 3). b, Monocytes and BEAS-2B cells were analyzed for expression of CD36 and TLR2 by flow cytometry (dashed line: isotype control). Additionally, BEAS-2B cells were transfected with CD36 or TLR2 expression plasmids (thick line, one of at least three independent experiments). Expression of CD36 was also verified by Western blotting (inset, c: control). c, BEAS-2B cells were transfected with TLR2 and CD36 expression plasmids as indicated. Twenty-four hours posttransfection, cells were left untreated or stimulated with 10 µg/ml LTA, P3C, P2C, 1 µg/ml R-FSL and S-FSL, inactivated S. aureus (MOI 100), or 10 ng/ml IL-1beta overnight, and IL-8 was quantified in cell-free supernatants (mean + SD). d, BEAS-2B cells were stimulated for the indicated time periods with 100 ng/ml TNF-{alpha} and IFN-{gamma}. Subsequently, TLR2 mRNA expression was examined by quantitative RT-PCR (mean + SD). e, BEAS-2B cells were prestimulated with TNF-{alpha} and IFN-{gamma} for 24 h, after which cells were washed and further stimulated as indicated for 18 h. IL-8 secretion was measured in the supernatant (mean + SD).

 
Induction of common and specific inflammatory programs by different airway pathogens

Having established that bronchial epithelial cells are able to recognize microbes using pattern recognition receptors (PRRs) we next asked whether pathogen-specific response patterns could be observed at the level of the transcriptome. We also sought to determine whether the tested S. aureus, which was poor in induction of IL-8, was able to induce a different set of genes. To evaluate this, we stimulated BEAS-2B cells with bronchial pathogens, including S. aureus, P. aeruginosa, and RSV that among other receptors can strongly activate TLR2, TLR4, and TLR3, respectively. Cellular RNAs from triplicate stimulations were analyzed at the genome wide level by microarrays. Using the Significance Analysis of Microarrays multiclass algorithm and significance thresholds of q = 1% (false discovery rate) and max (all averages)/min (all averages) >2 we found that ~520 individual genes were regulated (701 probe sets). Using hierarchical clustering, as well as the Tukey-Honest Significance Differences Test (Fig. 4, a and b), we first observed that S. aureus was nearly inactive with only a minor number of genes being regulated. This confirmed the findings of missing induction of IL-8 and points toward a general difference in recognition capacities of bronchial epithelial cells to different pathogens. In contrast, P. aeruginosa, as well as RSV, increased or decreased the expression of a considerable amount of genes. Regarding the genes, which were equally up-regulated (cluster 1 and 2) or down-regulated (cluster 5), by both pathogens, we identified a core group, which comprised 86 individual genes. Additionally, RSV and P. aeruginosa-specific response patterns were found to exist, with a large group of probe sets regulated preferentially by RSV (cluster 4, 6b) and a more limited P. aeruginosa selective response (cluster 3). Finally, transcription of a group of 40 genes was regulated in different directions by the two pathogens (cluster 6a). Prototypic microarray data were additionally examined by quantitative RT-PCR, which confirmed the existence of commonly, as well as specifically, regulated genes in response to P. aeruginosa and RSV (data not shown). Moreover, quantitative RT-PCR data indicate that among the commonly regulated genes different kinetic pattern exist (Fig. 4c, cmp. SOD2, ICAM1 vs IL8, CCL20).


Figure 4
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  		FIGURE 4. Common and unique changes in expression levels induced by infection. BEAS-2B cells were incubated with P. aeruginosa, S. aureus or RSV for 4 h and subsequently a genome-wide transcriptional analysis was performed. a, Hierarchical clustering of 701 probe sets induced or repressed upon infection (z-score normalized average expression values), and (b) Venn diagrams showing the numbers of up- and down-regulated individual genes for the different treatment conditions as determined with the Tukey-Honest Significant Differences Test. c, Expression of exemplary core response genes was measured by quantitative RT-PCR after stimulation of BEAS-2B cells for the indicated time intervals. Displayed are changes in expression as compared with the nonstimulated control of the respective time point (one of two experiments, dotted line indicates no change in expression). d, Heat maps visualizing the logarithm of fold changes in expression of IFN type I-induced genes (left) and genes annotated as having phosphatase activity (right). Only genes that showed significant regulation were included in this analysis.

 
The common response pattern of BEAS-2B cells comprised 86 individual genes of which 79 were up-regulated and 7 were down-regulated. Analysis of the genes indicated that they served three major functions: inflammatory signaling, cellular attraction and regulation of apoptosis (Table I, Supplemental Table IIa, d).4 Genes included chemokines, proinflammatory cytokines, and intracellular signaling molecules of defense pathways.


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  		Table I. Core response to Pseudomonas aeruginosa and RSVa

 
Regarding the specific response pattern to P. aeruginosa, we observed that additional genes necessary for inflammation, cellular attraction, and antiapoptosis were activated (Supplemental Table IIb); among these were IL1A and IL1B, which were not induced by RSV. Moreover, a prominent group of type I IFN-inducible genes (IFN {alpha} receptor 2, IFN-stimulated gene 20 kDa, IFN-induced protein with tetratricopeptide repeats 1, and IFN-induced protein with tetratricopeptide repeats 3) was induced, which may mean there is a correlation with the activation of the TLR4-Toll/IL-1 receptor domain-containing adapter inducine IFN-beta] IFN axis (Fig. 4d). Gene ontology analysis indicated the overrepresentation (at least five genes found per category and z-score > 5) of genes connected to inflammation, innate immunity, antiapoptosis, pathogen defense, chemotaxis, and response to wounding (Supplemental Table IIe). In contrast, many of the genes regulated by RSV belonged to the fields of regulation of transcription, regulation of nucleic acid metabolism and antiapoptosis, thus reflecting the needs of a replicating virus (Supplemental Tables IIc, f). This was also reflected by the fact that RSV induced much more genes than P. aeruginosa. Despite regulating genes required for transcription and replication, RSV also specifically induced genes associated with inhibitory effects in innate immune responses. Thus, a variety of inhibitory signaling molecules, including several members of the dual specificity phosphatase family and other phosphatases (PPM1D, PPP1R15A, PTP4A1, and PPAP2B), were induced (Fig. 4d). Although RSV replication results in dsRNA, which should activate the TLR3-TRIF axis, compared with P. aeruginosa RSV failed to induce many type I IFN-dependent genes (Fig. 4d).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Disclosures
 References
 
The results presented here show that bronchial epithelial cells in addition to their well-known function of continuously mounting a hostile environment for airborne microbes are able to recognize invading pathogens and to induce a pathogen-adopted response. To accomplish this, they make use of a common principle in innate immunity, the expression of pattern recognition receptors.

In detail we were able to observe functional expression of different TLRs as indicated by RT-PCR experiments and functional responses to the carefully characterized specific ligands. In agreement with others (4, 7, 13, 20, 21, 31), we also observed functional TLR1, TLR2, and TLR6 (lipopeptides), TLR3 (poly(deoxyinosinic-deoxycytidylic acid)), TLR4 (LPS), and TLR5 (flagellin; data not shown). We could not detect TLR7 and TLR8 and consistently ssRNA, as well as R848, were not active. Similar results were obtained in A549 cells (21, 32). Others reported TLR7 and TLR8 mRNA expression in 16-HBE cells, yet no functional data with specific ligands were shown (31). This indicates that different cell types are able to express sets of PRRs that serves the specific needs at the respective location. Furthermore, transcripts of other PRRs were also detected, yet the functional expression could have only been proven for NOD1. Recently, further cytosolic recognition proteins for RNA (MDA5 and RIG-I) and other pathogen-associated molecular patterns (e.g., NODs and NALPs) have been described (33, 34, 35), whether these proteins also play a role in epithelial cells remains unclear at the moment.

The important new information from our experiments comes from the fact that we observed different sensitivity to various TLR2-dependent ligands. In fact, bronchial epithelial cells express functional TLR2 as proven by positive responses to P3C, yet other TLR2 ligands (LTA, S-FSL) only weakly activated the cells. A low responsiveness of lung epithelial cells to LTA has also been observed by others (36). As the underlying mechanism, we can show that low expression of TLR2 and missing expression of the coreceptor CD36 results in hyporesponsiveness to certain TLR2 ligands. Interestingly, this correlated with hyporesponsiveness to whole Gram-positive bacteria, whereas Gram-negative bacteria with typical LPS molecules were uniformly stimulative. Further corroborating these findings, we observed that RSV and P. aeruginosa activated MAPKs and NF-{kappa}B, whereas S. aureus was only marginally active (our unpublished data). Similarly, it was also reported that intestinal epithelial cells display TLR2 unresponsiveness (16), and this was due to low expression of TLR2 and TLR6, as well as high levels of inhibitory Tollip. In this report, transgenic expression of TLR2 rescued TLR2 responses similarly to our own experiments. However, in our setting, CD36, which is a known coreceptor for some TLR2 ligands (19), played an additional role. TLR2 up-regulation as induced by proinflammatory cytokines TNF-{alpha} and IFN-{gamma} was not sufficient to restore full TLR2 sensitivity (for LTA). Moreover, we did not find high levels or induction of Tollip, a known inhibitor of TLR signaling (37). These results identify the level of receptor expression as an important restriction point in TLR signaling. More generally, this could serve to adapt microbe recognition to the needs of different compartments. This means that in sterile compartments every microbial compound is indicative of infectious danger and should be sensed by innate immune cells. In contrast, surfaces constantly exposed to microbial patterns should avoid recognition. It has been suggested that this is achieved by lack of surface expression for TLR4 and TLR5 in enterocytes (9, 10, 15). Also, down-regulation of central signaling molecules silences intestinal epithelium for recognition of apical bacteria (11). In a similar way, our results support the concept that in airway epithelium low TLR2 expression might play a role in limiting uncontrolled activation by inhaled bacteria. Gram-positive bacteria, known to consist of molecules activating TLR2 (16, 38, 39, 40, 41), thus do not easily induce epithelial activation. In contrast, bacteria rich in typical LPS, which are rarely found in airways, do so. Interestingly, some Gram-negative bacteria within the oral cavity also seem to avoid recognition via TLR4 by synthesizing atypical LPS structures that bind TLR2 as exemplified for Porphyromonas gingivalis (42, 43). Thus, regulating TLR expression levels serves as a mechanism for adjusting sensitivity of microbial recognition in different compartments (15). Whether the missing presence of TLR7 and 8 serves a similar function is not clear yet but has been consistently observed by others (21, 32).

A second important finding of this study is the observation that common, as well as specific, response patterns upon recognition of pathogens are induced here for RSV and P. aeruginosa. Similar findings have also been obtained for dendritic cells and viruses, fungi and bacteria (22), as well as for macrophages and defined TLR ligands (23, 44). We have identified a set of commonly induced genes, which represents the core response of epithelial cells to microbial danger and which included genes with function in inflammation, cellular attraction, and regulation of apoptosis. Many of these genes are known to be NF-{kappa}B dependent, and accordingly, NF-{kappa}B modulation in airway epithelium has been reported to impact defense of P. aeruginosa (45). A specific response signature of epithelium seems to be the induction of genes involved in cellular attraction, which subsequently orchestrates a developing inflammatory response. These findings have been confirmed by the use of bone marrow chimeras in which resident pulmonary cells contributed to the recruitment of neutrophils (46). Taken together, these findings ascribe to epithelium the property to mount a response that is partly adapted to a certain pathogen. This can be achieved by use of different adaptor proteins in TLR signaling (47), and accordingly, we find that P. aeruginosa shows activation patterns indicative of stimulation of MyD88 and TRIF pathways. Furthermore, coreceptors play an essential role in the modification of PRR responses. Recently, CD36 has been shown to act as accessory molecule for TLR2 responses to R-MALP2, LTA, and S. aureus but not for P3C (19). This fits to our findings where missing expression of CD36 results in hyporesponsiveness to LTA and S. aureus but not to P3C. Also, we observed different activities of R- and S-enantiomers of FSL-1 lipopeptides with R-FSL-1 being active but S-FSL-1 not. This is just opposite as reported for MALP2 enantiomers, with the reason therefore currently being unknown. We can further show by transfection studies that missing CD36 is an additional factor in hyporesponsiveness of BEAS-2B cells to TLR2 ligands. Moreover, it has been reported that CD36 is also of crucial importance in sensing and phagocytosis of whole S. aureus and thereof derived LTA (48). This further corroborates our findings of nonresponsiveness of bronchial epithelium to LTA, as well as staphylococci, which is also reflected in the gene array data. Similarly, we observed that zymosan did not activate BEAS-2B cells. Again missing expression of a coreceptor (49), here, dectin-1 might be an explanation for this finding. Thus, coreceptor expression is a mean to modify the pattern of microbial sensitivity.

Our results are not easy to reconcile with recent experiments showing activation of human bronchial epithelium or IHAEo– by streptococci (50) and staphylococci (51); however, experiments differed in the exact design. Moreover, we made use of a variety of different bacteria that allowed us to compare and to evaluate the magnitude of immune responses. The magnitudes of the observed immune responses were consistently low (but not absent) for the used Gram-positive bacteria and gene-array analysis confirmed findings on the genomic scale. In contrast, we found that all of the bacteria and TLR ligands were active in terms of immunostimulation when using CD14+ monocytes. This again supports a concept of regulating PRR sensitivity in different compartments.

Our gene array data additionally indicate that pathogens can circumvent immune recognition. To this end, RSV activates a set of inhibitory phosphatases, including the dual specificity phosphatase family that has recently been shown to negatively regulate LPS induced genes (52). The data also show that RSV fails to elicit an IFN response in bronchial epithelial cells. In support of these findings, it has been shown that in airway epithelial cells RSV inhibits the IFN-JAK-STAT axis via degradation of STAT2 (53).

Taken together, the experiments show that bronchial epithelial cells display a hyporesponsiveness to certain TLR2 ligands and S. aureus, which is due to low or missing expression of TLR2 and the coreceptor CD36. This might serve the specific needs of the host-microbial interface in the airways. Moreover, sensing pathogens results in the induction of shared as well as pathogen-specific inflammatory programs.


   Acknowledgments
 
We thank Adelina Dillmann, Stefanie Penati, and Angela Servatius for excellent technical support. We also appreciate scientific advice by Dr. Sonja Steppan.


   Disclosures
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
References
 
The authors have no financial conflict of interest.


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 This project was supported by grants of the Deutsche Forschungsgemeinschaft to A.H.D. (DFG Da 592/1 and /2) and R.B. (DFG 1641/6). The Microarray and Bioinformatics Core Unit at the Institute of Medical Microbiology, Immunology and Hygiene is supported in part by the Bundesministerium für Bildung und Forschung National Genome Research Network Infection and Inflammation FKZ 01GS0402, TP 37 to R.L.). Back

2 Address correspondence and reprint requests to Dr. Alexander H. Dalpke, Department of Medical Microbiology and Hygiene, Hygiene-Institute, University Heidelberg, Im Neuenheimer Feld 324, Heidelberg, Germany. E-mail address: alexander.dalpke{at}med.uni-heidelberg.de Back

3 Abbreviations used in this paper: LTA, lipoteichoic acid; MDP, muramyl dipeptide; MOI, multiplicity of infection; RSV, respiratory syncytial virus; DAP, diaminopimelic acid; P2C, Pam2CysSK4; P3C, Pam3CysSK4 pI:C, poly(deoxyinosinic-deoxycytidylic acid); PRR, pattern recognition receptors. Back

4 The online version of this article contains supplemental material. Back

Received for publication June 23, 2006. Accepted for publication December 18, 2006.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 

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