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Keywords:

  • airway epithelial cells;
  • cytokines;
  • grass pollen extract;
  • microarray;
  • Phl p 1

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

By definition, allergens are proteins with the ability to elicit powerful T helper lymphocyte type 2 (Th2) responses, culminating in immunoglobulin (Ig)E antibody production. Why specific proteins cause aberrant immune responses has remained largely unanswered. Recent data suggest that there may be several molecular paths that may affect allergenicity of proteins. The focus of this study is the response of airway epithelium to a major allergen from Phleum pratense Phl p 1. Instead of focusing on a few genes and proteins that might be affected by the major allergen, our aim was to obtain a broader view on the immune stimulatory capacity of Phl p 1. We therefore performed detailed analysis on mRNA and protein level by using a microarray approach to define Phl p 1-induced gene expression. We found that this allergen induces modulation and release of a broad range of mediators, indicating it to be a powerful trigger of the immune system. We were able to show that genes belonging to the GO cluster ‘cell communication’ were among the most prominent functional groups, which is also reflected in cytokines and chemokines building centres in a computational model of direct gene interaction. Further detailed comparison of grass pollen extract (GPE)- and Phl p 1-induced gene expression might be beneficial with regard to the application of single components within diagnosis and immunotherapy.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

Allergens are defined as proteins that have the ability to elicit powerful T helper lymphocyte type 2 (Th2) responses, culminating in immunoglobulin (Ig)E antibody production. Why specific proteins cause such an aberrant T and B cell response has remained largely unanswered. Recent data suggest that there may be several molecular paths that may affect allergenicity of proteins. These paths seem to depend on some intrinsic biological activity of the allergens, indicating that allergens can be more than passive players whose sole function is to cross-link IgE-molecules on the cell surface of mast cells.

Proteolytic activity as a general feature of major allergens has been proposed to be involved in the pathogenesis of allergies by enabling the passage of allergens through the epithelial barrier, cleaving adhesion molecules and affecting the functions of various cells and immune responses [1–4].

Recently it has become apparent that some allergen-binding lipids may contribute to the allergenicity of these proteins by affecting the response of cells to these lipids. For instance, Der p 2 was identified to resemble an important co-factor for Toll-like receptor (TLR)-4 signalling (MD-2), not only structurally but also functionally [5,6]. Several other members of the MD-2-like lipid-binding family are major allergens [7], referring to a more general importance of major allergens being able to bind lipids. Furthermore, a broad role for complex carbohydrates, in particular glucans, in allergen-associated Th2 responses is emerging [8].

However, the allergenicity of these proteins might be independent of their intrinsic biological function. Co-exposure of a tolerogenic protein with a protease can induce allergic sensitization so that environmental proteases derived from bacterial or viral origin might have accessory roles. Furthermore, microorganism-derived components, usually present in allergen extracts, could act as adjuvants with regard to the induction of immune responses.

Due to recent publications there is a growing awareness of the role of structural cells concerning allergen-induced immune responses. In particular, respiratory epithelium is likely to be important within the process of sensitization. It is accepted to be an active player in the response to the biological activity of aeroallergens, where they contribute to the immunological response by generating a microenvironment for the attraction and regulation of the activity of immune competent cells [9–12].

The focus of this study is the response of airway epithelium to the purified major allergen Phl p 1. Instead of focusing on a few genes and proteins that might be affected by the major allergen, our aim was to obtain a broader view on the immune-stimulatory capacity of Phl p 1. Furthermore, the detailed investigation of the gene expression and mediator release induced by the single major allergen might provide new insights into the contribution of the major allergen to the grass pollen extract (GPE)-induced response of airway epithelium. We therefore performed a detailed analysis on mRNA and protein level by using a microarray approach to define Phl p 1-induced gene expression to define the contribution of the purified major allergen to the induced allergic response.

Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

Cell culture

NCI-H292 human airway epithelial cells (American Type Culture Collection, Manassas, VA, USA) were cultured in RPMI-1640 medium (Invitrogen, Breda, the Netherlands) supplemented with 1·25 mm of l-glutamine, 100 U/ml penicillin, 100 µg/ml streptomycin and 10% (v/v) fetal bovine serum (HyClone, Logan, UT, USA). Cells were grown in fully humidified air containing 5% CO2 at 37°C and were subcultured weekly.

Experimental set-up

NCI-H292 cells were cultured in six-well plates to 80% confluence. Before stimulation, culture medium was removed and the cells preincubated with Hanks's balanced salt solution (HBSS) for 24 h. Cells were then stimulated with grass pollen major allergen Phl p 1 (5 µm) diluted in HBSS or with HBSS alone; 24 h after stimulation supernatants were collected and stored for further analysis. The cells were used for RNA isolation.

Preparation and purification of Phl p 1

Timothy grass pollen major allergen Phl p 1 was purified from pollen (ARTU Biologicals, Lelystad, the Netherlands), as described previously [13,14].

RNA isolation

Total RNA from each sample was extracted using Trizol (Life Technologies, Inc., Gaitersburg, MD, USA), according to manufacturer's instructions, followed by purification by nucleospin RNA II (Machery-Nagel, Düren, Germany). Concentration of extracted RNA was measured on the nanodrop ND-1000 (NanoDrop Technologies, Inc., Wilmington, DE, USA). RNA quality was checked by using Agilent 2100 bio-analyser (Agilent Technologies, Palo Alto, CA, USA).

Microarray Affymetrix U133 plus 2

Human Genome U133 Plus 2·0 Genechip Array (Affymetrix, Inc., Santa Clara, CA, USA) was used to analyse Phl p 1-induced gene expression. The technical handling was performed at the MicroArray Department at the University of Amsterdam (Amsterdam, the Netherlands), a fully licensed microarray technology centre for Affymetrix Genechip® platforms and official Dutch Affymetrix Service Provider, as described previously [15].

Microarray data analysis and statistics

Experiments were performed in triplicate and simultaneously. Gene chip images and data sets were uploaded into the server of the Netherlands Bioinformatics Center using the Rosetta Resolver Biosoftware package, which was also used for statistical analysis. Triplicates were compared in a factorial design using an error-weight one-way analysis of variance (anova). The quality of the images was checked by visual inspection and all raw data passed the quality criteria for average background, scale factors, percentage present calls, 3′/5′ ratios glyceraldehyde 3-phosphate dehydrogenase (GAPDH), 3′/5′ ratios beta-actin, hybridization spike-in controls and poly-A spike-in controls. The data also passed a set of quality control checks provided by the affy, affyPLM and affyQCreport packages from Bioconductor (http://www.bioconductor.org/). Expression values were calculated using the robust multi-array average (RMA) algorithm [16]. Statistical analysis for differential gene expression was performed using anova (maanova package, version 0·98·8 [17]). The permutation-based Fs test was used for hypothesis testing [18] and all P-values were adjusted for false discovery rate correction [19]. For gene ontology and network interaction analysis, GeneSpring GX11 (Agilent Technologies) was used. Correlations between observed fold changes within the microarray data and real-time PCR data were determined using Pearson's correlation.

Real-time PCR

Quantitative real-time PCR was performed with the Light Cycler 2·0 System (Roche Diagnostics, Mannheim, Germany) using LightCycler® Fast Start DNA MasterPLUS, according to the manufacturer's instructions. Relative cDNA amount was calculated compared to the expression of the housekeeping gene hypoxanthine–guanine phosphoribosyltransferase (HPRT).

Protein multiplex Luminex Bio-Plex assay

Cell free supernatants of Phl p 1- and control-treated cells were stored at −20°C until analysis. Cytokine levels in the supernatants of the treated cells were determined using a Bio-Plex Human Cytokine 30-Plex Panel Kit in combination with a Bio-Plex workstation (Bio-Rad, Veenendaal, the Netherlands). All standards were diluted in HBSS. Concentrations were calculated from a dilution series of standards using the Luminex software. Fold changes (FC) were calculated compared to the detected release in control-stimulated cells. If the measured mediator concentration in the control was below the detection level, the FC was calculated on basis of the detection limit for the respective mediator.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

Phl p 1-induced changes in gene expression level in airway epithelial cells

The overall gene expression ratio between HBSS and Phl p 1-stimulated cells was measured and calculated using the Rosetta resolver software. Expression was considered to be expressed significantly differentially with P ≤ 0·01 after one-way Bonferroni multiple test correction. The Affimetrix U133 plus 2·0 contains 54·675 transcripts, representing about 38 500 genes. Stimulation of NCI-H292 cells with Phl p 1 induced a huge response. In total, 7218 transcripts showed a significant regulation of gene expression. The subsequent analysis of transcripts, that were changed by more than threefold, revealed 86 transcripts to be up-regulated and 16 transcripts to be down-regulated, corresponding to 54 and 11 known genes, respectively.

For validation of the microarray data we first investigated the influence of stimulation with Phl p 1 on the expression of housekeeping genes. Analysing the expression of these genes revealed that their regulation is not affected by stimulation with Phl p 1. For example, the average expression ratio between control and stimulated condition for GAPDH has been 1·03 (±0·00), and beta-2 microglobulin (B2M) showed a fold change of 0·90 (±0·01). To confirm further the observed expression levels, we chose 11 genes from the 65 known genes that showed an up- or down-regulation by more than threefold for confirmatory real-time polymerase chain reaction (PCR). In Table 1 the ratios calculated from the microarray data and the real-time PCR derived expression ratios are shown. Expression levels derived from real-time PCR were calculated as fold change between control and Phl p 1-stimulation and normalized to GAPDH and HPRT. The real-time PCR data strongly resemble the ratios calculated on the basis of the microarray data (see Fig. 1). Statistical analysis of the two sets of data revealed a high correlation (R = 0·79 with R2 = 0·63), pointing towards a correlation of 63% between the microarray data and the results of the real-time PCR.

Table 1.  Validation of the Phl p 1-induced expression profile of selected genes using real-time polymerase chain reaction (PCR). All values are given as mean (± standard deviation). Real-time PCR values are stated as fold change between control and Phl p 1-stimulated cells and normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and hypoxanthine–guanine phosphoribosyltransferase (HPRT).
GeneMicroarray ratioReal time-PCR (fold induction)
CCL 2010·9 (±0·1)50·2 (±7·8)
IL-87·4 (±0·1)8·9 (±4·2)
IL-13RA212·8 (±1·0)n.d.
SERPINB47·3 (±0·2)7·1 (±1·9)
TNFAIP63·0 (±0·1)14·3 (±1·8)
COL8A111·9 (±1·2)22·1 (±3·3)
VTCN1−3·4 (±0·3)−8·0 (±1·8)
PTGS24·8 (±0·2)8·9 (±0·6)
CXCL26·4 (±0·1)9·0 (±3·1)
CXCR46·0 (±0·2)9·5 (±3·0)
TGF-B23·7 (±0·05)3·6 (±0·8)
image

Figure 1. Correlation plot of real-time polymerase chain reaction (PCR) data and microarray results. Correlations between observed fold changes within the microarray data and the real-time PCR data were determined using Pearson's correlation.

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After successful validation of the microarray data we continued with sorting the genes that were regulated at least threefold up or down after stimulation with Phl p 1 into functional classes. Using their ascribed gene ontology, genes were assorted by their molecular function or the biological process in which they are involved (Table 2). After correcting the assorted gene categories for the group ‘unclassified genes’, we found 10 genes (16·4%) to be in the group ‘immunity and defence’, four genes in the group ‘receptor activity’, ‘enzyme inhibitor activity’ (two) and ‘ion binding’ (three). Comparable to previous results we obtained with GPE the groups ‘cell communication’, representing cytokines, chemokines and growth factors, and ‘metabolism’ appeared to be the most prominent ontology groups, with 23 genes (38%) and 16 genes (26·2%), respectively. All genes identified to be single members of a certain ontology group were pooled within the category ‘miscellaneous’.

Table 2.  Genes expressed differentially in NCI-H292 cells after stimulation with Phl p 1, sorted by ontology into functional groups. Stated are gene aliases, fold changes calculated in relation to control-stimulated cells, gene names, P-values and accession numbers.
Gene aliasFold changeGene name/descriptionP-valueAccession no.
  1. Table indicates gene aliases, fold change, gene name, P-value and gene ID.

Cell communication    
 COL8A111·9Collagen, type VIII, alpha 11·54E-06226237_at
 IL611·2Interleukin 6 (interferon, beta 2)4·48E-08205207_at
 CCL2010·9Chemokine (C-C motif) ligand 205·91E-09205476_at
 IGFBP58·0Insulin-like growth factor binding protein 51·65E-08211959_at
 IL87·4Interleukin 82·88E-08211506_s_at
 EREG7·2Epiregulin8·94E-08205767_at
 CXCL26·4Chemokine (C-X-C motif) ligand 24·48E-08209774_x_at
 NRP25·9Neuropilin 23·46E-06222877_at
 CXCL15·5Chemokine (C-X-C motif) ligand 13·00E-08204470_at
 IGFL15·3IGF-like family member 15·54E-07239430_at
 RCAN13·9Regulator of calcineurin 11·25E-07208370_s_at
 BCL2A13·9BCL2-related protein A12·07E-06205681_at
 TGFB23·7Transforming growth factor, beta 21·16E-07209909_s_at
 PRKAR2B3·6Protein kinase, cAMP-dependent, regulatory, type II, beta1·54E-06203680_at
 IL1A3·6Interleukin 1, alpha2·78E-07210118_s_at
 IL1B3·6Interleukin 1, beta4·95E-0839402_at
 MCAM3·4Melanoma cell adhesion molecule2·65E-07211340_s_at
 GJB23·3Gap junction protein, beta 2, 26 kDa1·25E-05223278_at
 BIRC33·3Baculoviral IAP repeat-containing 34·94E-07210538_s_at
 CXCL33·2Chemokine (C-X-C motif) ligand 34·83E-07207850_at
 RAB27A3·2RAB27A, member RAS oncogene family2·63E-07210951_x_at
 TSHZ23·1Teashirt zinc finger homeobox 29·65E-05232584_at
 BOLA3−3·6BolA homologue 3 (Escherichia coli)7·78E-08227291_s_at
Immunity and defence    
 TNC6·3Tenascin C (hexabrachion)2·30E-08201645_at
 SAA25·7Serum amyloid A24·95E-08208607_s_at
 KLRC25·3Killer cell lectin-like receptor subfamily C, member 25·63E-06206785_s_at
 SGK13·5Serum/glucocorticoid regulated kinase 11·90E-06201739_at
 KLRC33·3Killer cell lectin-like receptor subfamily C, member 31·24E-05207723_s_at
 TNFAIP63·0Tumour necrosis factor, alpha-induced protein 62·02E-05206026_s_at
 OAS13·22′,5′-oligoadenylate synthetase 1, 40/46 kDa5·92E-06205552_s_at
 DEFB1−3·1Defensin, beta 14·34E-06210397_at
 DTL−3·2Denticleless homologue (Drosophila)1·11E-05218585_s_at
 VTCN1−3·4V-set domain containing T cell activation inhibitor 17·74E-06219768_at
Receptor activity    
 IL13RA212·8Interleukin 13 receptor, alpha 22·34E-07206172_at
 CXCR47·8Chemokine (C-X-C motif) receptor 41·10E-07217028_at
 ITGB83·5Integrin, beta 82·87E-06205816_at
 BDKRB13·1Bradykinin receptor B13·57E-07207510_at
Enzyme inhibitor activity    
 SERPINB410·0Serpin peptidase inhibitor, clade B (ovalbumin), member 45·91E-09211906_s_at
 SERPINB34·0Serpin peptidase inhibitor, clade B (ovalbumin), member 37·74E-08209719_x_at
Metabolism    
 AKR1C216·0Aldo-keto reductase family 1, member C26·42E-081562102_at
 AKR1C16·6Aldo-keto reductase family 1, member C15·91E-09204151_x_at
 AKR1B15·4Aldo-keto reductase family 1, member B1 (aldose reductase)2·30E-08201272_at
 PTGS25·5Prostaglandin–endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase)1·27E-061554997_a_at
 SOD24·8Superoxide dismutase 2, mitochondrial1·65E-08215223_s_at
 MRPS64·7Mitochondrial ribosomal protein S62·58E-05213167_s_at
 HS3ST14·1heparan sulphate (glucosamine) 3-O-sulphotransferase 18·05E-06205466_s_at
 FST3·8Follistatin6·03E-08207345_at
 PGM2L13·7Phosphoglucomutase 2-like 13·00E-08229256_at
 DIO23·6Deiodinase, iodothyronine, type II8·39E-05203699_s_at
 SLC5A33·4Solute carrier family 5 (inositol transporters), member 31·90E-071553313_s_at
 SEPP1−3·1Selenoprotein P, plasma, 13·57E-07201427_s_at
 EMP1−3·2Epithelial membrane protein 11·64E-06201324_at
 ALDH1L2−3·4Aldehyde dehydrogenase 1 family, member L21·39E-06231202_at
 CLYBL−5·0Citrate lyase beta-like3·57E-07238440_at
 KRT4−5·3Keratin 41·43E-07213240_s_at
Ion binding    
 TCHH9·6Trichohyalin6·00E-09213780_at
 KCNK37·2Potassium channel, subfamily K, member 31·82E-06205952_at
 TESC5·4Tescalcin1·83E-07218872_at
Miscellaneous    
 TMEM465·3Transmembrane protein 465·71E-08230493_at
 IER35·8Immediate early response 32·79E-08201631_s_at
 FRMD33·7FERM domain containing 35·55E-06230645_at
Unclassified    
 LOC38776310·0Unknown2·30E-08227099_s_at
 1555854_at8·4Unknown5·66E-081555854_at
 229242_at6·9Unknown7·53E-09229242_at
 C20orf1754·7Chromosome 20 open reading frame 1751·14E-05227654_at
 226560_at4·4Unknown1·24E-07226560_at
 C8orf43·7Chromosome 8 open reading frame 41·21E-07218541_s_at
 LOC6456383·6Similar to WDNM1-like protein6·03E-08229566_at
 CXorf583·4Chromosome X open reading frame 581·04E-051553391_at
 243509_at3·4Unknown3·14E-05243509_at
 C13orf153·3Chromosome 13 open reading frame 157·42E-06218723_s_at
 C6orf1553·2Chromosome 6 open reading frame 1551·46E-05220324_at
 230356_at3·2Unknown2·81E-07230356_at
 C11orf70−3·2Chromosome 11 open reading frame 709·07E-07224463_s_at
 228661_s_at−3·4Unknown3·18E-06228661_s_at
 KANK4−3·5KN motif and ankyrin repeat domains 41·82E-06229125_at
 1558605_at−3·5Unknown4·34E-061558605_at
 222288_at−3·6Unknown1·32E-07222288_at
 RCSD1−4·6RCSD domain containing 14·41E-06225763_at
 238632_at−4·6Unknown4·31E-06238632_at

Network analysis and Phl p 1-induced significant signalling pathways

To be able to identify interactions within genes that displayed an altered expression after stimulation with Phl p 1, we performed a network analysis· The evaluation of genes with a significant change in expression level by at least threefold up or down revealed 50 genes to interact directly, with 31 genes showing Phl p 1-induced changes in expression (Fig. 2). Resembling the observation that cell communication was identified to be among the most prominent GO groups, a predominant proportion of the genes in the network are related to chemokines and cytokines, with interleukin (IL)-1A, IL-1B, IL-6 and IL-8 forming hubs within the computational model.

image

Figure 2. Direct interaction network after stimulation of NCI-H292 cells with Phl p 1. Input has been all genes with significant up- or down-regulation by more than threefold (P ≤ 0·01, fold change ≥ 3·0). Genes are sorted by their cellular location and are coloured by their expression with green for down-regulation, red for up-regulation and grey for unaltered gene expression level.

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Next we analysed signalling pathways induced significantly after stimulation of NCI-H292 cells with Phl p 1. We therefore screened all significantly Phl p 1-regulated probe sets independent of their fold change for their participation in specific signalling cascades. As shown in Table 3, the following pathways appeared to be regulated by Phl p 1: epidermal growth factor receptor 1 (EGFR1), IL-1, IL-2, IL-3, IL-4, IL-6, IL-7, Notch, Wnt, transforming growth factor beta receptor (TGF-βR), tumour necrosis factor (TNF)-α, and nuclear factor kappa-light-chain enhancer of activated B cells (NF-κB).

Table 3.  Phl p 1-induced signalling pathways.
PathwayInvolved genes*Genes regulated by Phl p 1P-value
  • *

    Genes matched with Agilent technology. IL, interleukin; TNF, tumour necrosis factor; EGF, epidermal growth factor; NF-κB, nuclear factor kappa B.

EGFR1178674·26E-05
IL-124135·90E-03
IL-258283·96E-04
IL-371261·13E-02
IL-449173·01E-02
IL-652237·32E-04
IL-71696·32E-03
NOTCH74271·55E-02
TGFBR137499·98E-04
TNF-α/NF-κB193742·69E-07
Wnt105374·08E-03

Phl p1-induced protein expression

GO analysis indicated the group ‘cell communication’ to be the dominant functional group among Phl p 1-regulated genes. We therefore continued with the determination of Phl p 1-induced release of mediators in general. As shown in Table 4, measurement of the release of a panel of chemokines, cytokines and growth factors showed a massive Phl p 1-induced increased release of IL-1RA, IL-6 and IL-8, which was also reflected by a clear increase in gene expression levels. Albeit at rather low level, vascular endothelial growth factor (VEGF) showed an increase in release and also a moderate Phl p 1-induced up-regulation of gene expression. Granulocyte–macrophage colony-stimulating factor (GM-CSF), granulocyte colony-stimulating factor (G-CSF), epidermal growth factor (EGF), interferon gamma-induced protein IP-10 and monokine induced by gamma interferon (MIG) showed a moderate increase on mediator levels, with gene expression levels remaining unaltered upon stimulation. Although the monocyte chemotactic protein-1 (MCP-1) showed an increased release of 5·4-fold, the corresponding gene showed no altered expression upon stimulation, which is likely to result from the fact that 24 h were chosen for stimulation. IL-12 also showed a clear enhanced release upon stimulation, with an increase of detectable IL-12p40/p70 by fourfold. Interestingly, this was not reflected in the Phl p 1-induced expression level of the IL-12 gene, with IL12A (p35) and IL12B (p40) gene expression remaining unaltered. For IL-1β we were not able to detect an increased release, but the stimulation with Phl p 1 resulted in a clear up-regulation of gene expression by 3·6-fold, indicating IL-1β to be more probably part of a secondary response induced by Phl p 1. A similar picture emerged for TNF-α, IL-15 and fibroblast growth factor (FGF)-β that were also undetectable within the supernatant of Phl p 1-stimulated airway epithelial cells (AECs), with gene expression levels being only slightly up-regulated. IL-2R was identified to be released on basal level after stimulation with Phl p 1 and the gene expression level remained unaltered.

Table 4.  Mediator release from NCI-H292 cells after stimulation with Phl p 1 for 24 h. After stimulation cell free supernatants were collected and analysed for the presence of chemokines and cytokines. The stated values represent the average (± standard deviation) of a triplicate experiment and are given in pg/ml; with detection limits in brackets for each of the mediators. Fold change (FC) was calculated in relation to level of control-stimulated cells.
MediatorHBSS (ctrl)Phl p 1FC ELISAFC microarray
  • *P ≤ 0·01.

  • Not significant; n.d., not detectable; ELISA, enzyme-linked immunosorbent assay; HBSS, Hanks's balanced salt solution; IL, interleukin; TNF, tumour necrosis factor; MCP, major chemoattractant protein; GM-CSF, granulocyte–macrophage colony-stimulating factor; VEGF, vascular endothelial growth factor; FGF, fibroblast growth factor beta; EGF, epidermal growth factor; IP, interferon gamma-induced protein; MIG, monokine induced by gamma interferon; FC, fold change.

IL-1RA (14·2)165 (±53)1563 (±462)9·5 (±4·1)1·4*
IL-1β (5·8)11·7 (±0)13 (±2·2)1·1 (±0·2)3·6*
IL-2R (10·7)28 (±3)36·7 (±16·4)1·3 (±0·6)1·1
IL-6 (3·2)39 (±10·4)1855 (±686)48 (±22)11·2*
IL-8 (2·3)180 (±81)10160 (±0)56·5 (±25·3)7·6*
IL-12 (4·8)16·2 (±2·4)64 (±4·3)4 (±0·6)1·1
IL-15 (8·5)n.d.n.d.1·3*
TNF-α (2·6)n.d.n.d.1·2*
MCP-1 (3·9)204 (±57)1095 (±39)5·4 (±1·5)1·1
GM-CSF (9·4)19 (±0)29·5 (±9·5)1·6 (±0·5)1·1
G-CSF (6·2)22·2 (±9·4)43·7 (±8·7)2·0 (±0·9)1·0
VEGF (4·6)n.d.16·1 (±1·5)3·5 (±0·3)1·6*
FGF-β (8·2)n.d.n.d.1·3*
EGF (5·4)n.d.15·5 (±5)2·9 (±0·9)1·0
IP-10 (1·1)n.d.3·7 (±0·5)3·4 (±0·5)1·0
MIG (1·3)8·0 (±0·3)12·2 (±3·9)1·5 (±0·5)1·1

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

Although in this experimental set-up we stimulated AECs with a single component derived from GPE only, we still observed a huge number of Phl p 1-regulated genes and significant Phl p 1-induced release of mediators. In total, 7218 transcripts showed a significant regulation of gene expression, with 71 genes showing a Phl p 1-induced altered gene expression level of at least threefold. The observed extent of this response might result partially from the usage of the cell line NCI-H292. In previous studies we have already observed more pronounced fold changes and a higher number of affected genes in stimulated NCI-H292 cells when compared to the response induced in primary nasal epithelial cells [20]. Nevertheless, we decided to use this established model, as it offers the advantage of limited experimental variation and lack of potentially contaminating cells. The absence of intra-individual differences enables the detection of small changes in gene expression levels and therefore might add valuable information.

Phl p 1 has already been shown to induce an increased expression of IL-6, IL-8 and TGF-β from AECs on both mRNA and protein levels [13], but our data show the true extent of this response. Subsequent analysis of prominent GO clusters showed that the group ‘cell communication’ belongs to the most prominent Phl p 1-induced groups, reflecting the ability of the major allergen to induce the release of mediators that, in turn, can attract and influence the activity of immune-competent cells. On the assumption that the response of NCI-H292 cells has been shown to rather reflect the healthy epithelial immune response towards allergens [20], our data support the observation that epithelial cells from healthy donors release high levels of cytokines and chemokines upon stimulation with house dust mite extract (HDM) or birch pollen allergens [21,22].

Network analysis of direct interactions within genes that showed a change in gene expression level of at least threefold revealed central roles for IL1A, IL6, IL8, but also for IL1B. Phl p 1 induced a pronounced up-regulation of the expression of this proinflammatory cytokine (3·6-fold). Interestingly, polymorphisms within IL1B are associated with allergic rhinitis [23], confirming the importance of this mediator within atopic diseases. Vroling et al. already investigated the response of AECs to HDM allergens in detail on both a respiratory epithelial cell line and primary nasal epithelial cells from healthy donors and allergic individuals [20,24]. Network analysis of the aforementioned samples revealed a set of overlapping genes, describing an epithelial core-response towards HDM. Interestingly, some of these genes (namely IL1B, CXCL1, CCL20, IL8, CXCL2, PTGS2 and SERPINB3) were also regulated by Phl p 1 and part of the interaction network created upon genes that showed Phl p 1-induced alterations in expression level by at least threefold (Fig. 2). It is tempting to speculate about the existence of a general epithelial core-response towards aeroallergens, with genes being part of the core-response and genes showing changes in expression level upon stimulation with the respective allergenic extract that are specific for the source of allergens. Mutations within genes that are part of the core-response or mutations in genes that are induced specifically might explain why individuals become mono- or polysensitized. However, further experiments are required to follow this hypothesis.

Interestingly, the chemokine receptor CXCR4 displayed a pronounced up-regulation for both, GPE- and Phl p 1-stimulation of AECs. This receptor has been shown to be expressed on Th2 cells and is relevant during Th2-type allergic airway responses [25]. Besides its role as major co-receptor for HIV-entry [26], CXCR4 was also shown to be expressed in human intestinal epithelial cells and is up-regulated in inflammatory bowel diseases [27]. CXCR4 is functionally expressed on the cell surface of various immune cells and plays a role in cell proliferation and migration. This G-protein-coupled receptor (GPRC) is endocytosed upon activation. Furthermore, it has been shown that blocking of CXCR4 has a significant effect in down-regulating the inflammation of allergen-induced immune response [28]. Taken into account that agonist-occupied CXCR4 undergoes clathrin-dependent endocytosis in human epithelial cells [29,30], it is tempting to speculate that the massive up-regulation of CXCR4 we observed after stimulation of AECs with GPE (11·5-fold up) or Phl p 1 (7·8-fold up) might contribute to the epithelial uptake of grass pollen allergens. Furthermore, after stimulation of epithelial cells from allergic donors with the birch pollen major allergen Bet v 1 an over-representation of the GO terms ‘response to viruses’ and ‘cell receptors’ could have been detected [31,32]. However, further experiments are required to investigate this possible mechanism.

Many major allergens seem to posses functional attributes which may, at least partially, explain their allergenicity. It might well be that the immune activating molecules are not identical to the proteins triggering the allergic response, although this would still raise the question of why those particular proteins are recognized among the many present during exposure. Extracts from different pollen have been shown to cause detachment of airway epithelial cells dependent on a proteolytic activity of the extracts [33]. Also, the activating capacity of HDM extract and HDM allergens is caused probably by a proteolytic activity of the allergens with, for example, Der p 1 identified to be a serinprotease. Der p 1 has been shown to degrade tight junction proteins, thereby inducing the release of mediators and facilitating the route of the allergen through the epithelial barrier [34–36]. Although we were not able to observe any detachment of Phl p 1-stimulated AECs, members of the family of serinprotease inhibitors (SERPIN) showed an increase in gene expression level and CDH1, encoding for cadherin-1, a calcium-dependent cell–cell adhesion glycoprotein, appeared to be down-regulated upon stimulation with GPE by more than threefold. Phl p 1 is discussed to exert proteolytic activity, with a recombinant in Pichia pastoris expressed form acting as protease, whereas natural Phl p 1 failed to act as protease both in vitro and ex vivo[13]. In contrast to GPE-stimulated AECs, Phl p 1 only induced a moderate down-regulation of CDH1 (−1·5-fold), which might allow the suspicion that proteases potentially present within the whole extract might allow the passage of allergens (including Phl p 1) through the epithelial barrier by disrupting cell–cell adhesion.

However, regardless of the speculated ability to act as a protease itself, this major allergen induces the up-regulation and release of a broad range of mediators, indicating it to be a powerful trigger of the immune system. Taken together, we were able to show that the major allergen Phl p 1 induces a huge response in AECs, both on the gene expression level, as well as on the level of mediator release. Genes belonging to the GO cluster ‘cell communication’ were among the most prominent functional groups, which is also reflected in IL1A, IL1B, IL6 and IL8 building centres in a model of direct gene interaction of genes showing an altered gene expression level of at least threefold. Further detailed comparison of GPE-and Phl p 1-induced gene expression might be beneficial with regard to the application of single components within diagnosis and immunotherapy.

Acknowledgement

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

We thank Marisa Böttger (Research Center Borstel, Germany) for excellent technical assistance. This study was supported by Deutsche Forschungsgemeinschaft (DFG)-TR22-Z1/A3 and by the Interuniversity Attraction Poles Programme (IUAP) – Belgian state – Belgian Science Policy P6/35.

Disclosure

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References

None of the authors has any conflict of interest related to this manuscript.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Disclosure
  9. References