Celiac disease is a common autoimmune disorder of the small intestine, triggered and maintained by gluten in genetically predisposed individuals. The presence of human leukocyte antigen (HLA)-DQ2 or HLA-DQ8 is necessary for the initiation of the intestinal inflammation that ultimately results in total villous atrophy coupled with crypt hyperplasia (1). These HLA class II molecules are expressed in approximately one-third of the populations in which celiac disease is prevalent; however, less than one-tenth of the gene carriers develop celiac disease, implying that other genetic and environmental factors are involved in the pathogenesis (2).
Children with celiac disease have an almost 2-fold likelihood of being born by cesarean section when compared with healthy controls (3). Children born by cesarean section harbor different gut microbiota than those born vaginally (4). It is thus plausible to suggest that gut microbiota may have a role in the development of celiac disease. Studies addressing the issue have yielded inconsistent results so far (5–11).
A single layer of epithelial cells borders the small and large intestines as a barrier between commensal bacteria and the rest of the body. Toll-like receptors (TLRs) are located in intestinal epithelial cells and lamina propria, where they recognize different bacterial molecular patterns. This interplay promotes epithelial cell proliferation, secretion of immunoglobulin A, and expression of antimicrobial peptides (12). Dysregulation of this delicate microorganism-induced program of epithelial cell homeostasis results in chronic inflammatory responses seen, for example, in inflammatory bowel disease (12). Because the expression of microbiota and TLRs in celiac disease has not been studied concurrently, we evaluated microbiota, TLRs, and their regulators in the small intestinal biopsies from patients with celiac disease. In addition, the gene expression of interleukin-8 (IL-8), a chemokine recently suggested to play a crucial role in the intestinal inflammation in celiac disease, was characterized (13).
Three groups of patients were included in the study: 10 children (mean age 9.5 years, range 3–14 years) with newly diagnosed celiac disease before implementation of a gluten-free diet (untreated celiacs), 6 adults (46 years, range 30–60 years) who had been on a gluten-free diet at least for 1 year (treated celiacs), and 9 control children (8.5 years, range 4–16 years) (controls). All of the untreated celiacs had positive celiac serology markers (anti-tissue transglutaminase antibodies and/or anti-endomysium antibodies) and villous atrophy and crypt hyperplasia (Marsh III lesions) in small intestinal biopsy, whereas all of the treated celiacs and controls had negative celiac serology and normal small intestinal mucosa (Marsh 0 lesions) (14). The group of treated celiacs included adults only because a response to a gluten-free diet is ordinarily controlled in children in Finland merely by celiac serology. If celiac serology markers turn negative within the first year after the diagnosis, as was the case in all of the children with celiac disease in the study, then a follow-up endoscopy is omitted. Written informed consent was obtained from all of the study patients or their parents. The study was accepted by the ethical committee of the Hospital District of Southwest Finland.
RNA Isolation, Reverse Transcription Reactions, and Gene Expression Assays
Biopsy samples were washed with RNAase-free water and then immediately submerged in RNAlater RNA stabilization reagent (Qiagen, Hilden, Germany). After the incubation at 4°C for 1 day, the samples were stored at −20°C in RNAlater until RNA isolation. Before RNA isolation, the sample was weighed and subsequently homogenized using Ika Ultra Turrax T8 high-performance disperser (Wolf Laboratories, York, UK). RNA isolation was performed using RNeasy Plus Mini-kit (Qiagen) according to the kit's manual. Isolated RNA was eluted to a new RNAase-free tube with 30 μL of RNAase-free water and stored at −70°C. RNA concentration was measured by NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE), and the quality of RNA was analyzed with Bio-Rad Experion System (BioRad Laboratories, Hercules, CA). Only high-quality RNA was used in reverse transcription reactions, which were performed using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems/Life Technologies Corporation, Carlsbad, CA) according to the kit's manual. Two micrograms of RNA was used in the total reaction volume of 40 μL. Thermal cycler conditions used were 25°C for 10 minutes, 37°C for 120 minutes, 85°C for 5 seconds, and 4°C to the end of the run. The concentration of cDNA was calculated on the basis of the concentration of RNA. cDNA was stored at −20°C until gene expression assays.
Gene expression assays were performed using the comparative threshold cycle (Ct) method with the ABI 7300 Real-Time PCR System (Applied Biosystems). Taqman Gene Expression Assays (Applied Biosystems) used in analyses were IL-8, assay ID Hs00174103_m1; TLR2, assay ID Hs00610101_m1; TLR3, assay ID Hs00152933_m1; TLR4, assay ID Hs00152939_m1; TLR5, assay ID Hs00152825_m1; TLR9, assay ID Hs00152973_m1; Toll-interacting protein (TOLLIP), assay ID Hs00184085_m1; single immunoglobulin IL-1R–related molecule, assay ID Hs00222347_m1. Gene expression assays were performed according to the kit's protocol. Reactions were run in 3 replicates in a total volume of 50 μL with 25 ng of cDNA in each. Thermal cycler conditions used were 50°C for 2 minutes, 95°C for 10 minutes, 95°C for 15 seconds, and 60°C for 1 minute. Steps 3 and 4 were repeated 40 times. Gene expression of 18S RNA was used as an endogenous control (a housekeeping gene) because of its invariable expression in all of the samples used in the study. Negative control and Universal Human Reference RNA (Agilent Technologies, Santa Clara, CA) as a control RNA were included in every polymerase chain reaction (PCR) run. Results were analyzed with the RQ Study software program (Applied Biosystems) to receive Ct values for all of the samples. Threshold levels were first set automatically by the program, but in a few cases, the threshold level was corrected manually to be equal to all of the samples within the analyses of 1 gene, ensuring the comparative analysis of the samples. The relative expressions of genes were calculated according to the formulas provided by the manufacturer (Applied Biosystems) by normalization of sample Ct to the endogenous control (ΔCt) and further to the control RNA (ΔΔCt). Relative changes in gene expressions were then calculated using the formula 2−ΔΔCt.
DNA Extraction From Biopsy Samples by Using Bead Beating and the Qiagen Column
DNA was extracted essentially as described by Nylund et al (15) with some modifications to the protocol. The biopsy was weighed and immersed in 180 μL of enzymatic lysis buffer containing 20 mg/mL of lysozyme in 20 mmol/L Tris-HCl-2 mmol/L ethylenediaminetetraacetic acid-1.2% (w/v) Triton X-100 (Sigma-Aldrich, St Louis, MO). The sample was incubated for 30 minutes at 37°C. Subsequently, 25 μL of proteinase K and 200 μL of buffer AL (Qiagen) were added and the sample was mixed by vortexing and incubated at 56°C for 30 minutes. The sample was then transferred into a 2-mL screw-cap tube with 0.25 g of zirconia beads (0.1 mm, Biospec Products, Bartlesville, OK) and homogenized with 3 minutes of bead beating with FastPrep-24 (FP120–230; Bio 101 ThermoSavant, Holbrook, NY). Lysate fraction obtained from the homogenization step was transferred into a new tube and the DNA was isolated by using the Qiagen DNeasy mini-spin column (Qiagen) and following the manufacturer's protocol for Gram-positive bacteria. Finally, the DNA was eluted into 100 μL of buffer AE (Qiagen). The DNA concentration was measured with a NanoDrop ND-1000 spectrophotometer. The DNA extractions were stored at −20°C until use.
Quantitative PCR (qPCR) for bacteria, archaea, and different bacterial groups and species were performed with a set of specific primers, which have been described previously (Table 1) (16–25). qPCR analysis was carried out in a Applied Biosystems 7300 Fast Real-Time PCR System in a 96-well format and using SYBR Green chemistry (Power SYBR Green PCR Master Mix; Applied Biosystems). The total volume of qPCR reaction was 25 μL, using 1 μL of DNA sample or standard as a template. The primer concentrations and thermocycling programs were optimized for each specific PCR reaction. The optimized primer concentrations were between 0.1 and 0.5 μmol/L for each primer. The thermocycling programs were 95°C for 10 minutes, 40 cycles of 50°C to 65°C for 20 to 60 seconds, 72°C for 30 to 50 seconds, and 95°C for 15 to 20 seconds. Standards were prepared by amplifying the target DNA fragment from a pure culture of corresponding target organism and subsequently purifying the amplified fragment by using the QIAquick PCR purification kit (Qiagen). The concentration of the purified fragment was quantified by using the NanoDrop ND-1000 spectrophotometer, and the preparation was diluted appropriately for use as standards with a known number 16S rRNA, nuc or tuf gene fragment copies. Biopsy samples were assayed in duplicate and the results were analyzed using Applied Biosystems's 7300 Fast Real-Time PCR System SDS Software (version 1.4.0). Melting curve analysis was performed after the PCR to confirm the specificity of amplification. The amount of 16S rRNA, nuc or tuf gene copies of the specific bacterial groups or species in biopsy samples, was determined by comparing the Ct values of samples with those of the standard curves.
Due to non-normal distribution of the data, bacterial counts and relative gene expressions are presented as medians with 25th and 75th percentiles. Kruskall-Wallis 1-way analysis of variance was used in comparisons of untreated celiacs, treated celiacs, and controls. Comparisons between 2 different groups were made by the Mann-Whitney U test. A P value <0.05 was considered statistically significant. All of the statistical analyses were made by SPSS version 11.0.2 for Mac OS X (SPSS Inc, Chicago, IL).
Microbiota in the Small Intestinal Biopsies
Counts of total bacteria were 1723 (592–2692) 16S rRNA gene copies per milligram of tissue. The total bacterial counts were similar between untreated celiacs, treated celiacs, and controls (P = 0.31, data not shown). Different bacterial groups found in all of the subjects are presented in Table 2. All of these counts were comparable between the groups. The Bacteroides fragilis group, Bifidobacterium catenulatum group, B longum, and Streptococcus genus were found in a small number of biopsies, whereas Lactobacillus group, Staphylococcus aureus, and B longum subsp infantis were found in none of the biopsies (data not shown). There were no significant differences in the amounts or frequencies of these bacteria between the study groups.
Gene Expression in the Small Intestinal Biopsies
The gene expression of IL-8, as a marker of intestinal inflammation, was significantly increased in untreated celiacs as compared with treated celiacs and controls (Fig. 1). The expression of TLR-2 mRNA was decreased and the expression of TLR-9 mRNA was increased in untreated and treated celiacs as compared with controls (Figs. 2 and 3). In pairwise comparisons with controls, the gene expression of TLR2 was significantly decreased in both untreated and treated celiacs (Fig. 2), whereas that of TLR9 was significantly increased in untreated but not in treated celiacs (Fig. 3). The expression of TOLLIP mRNA, an inhibitor of TLR signaling, tended to be upregulated in controls as compared with untreated and treated celiacs (Fig. 4). In pairwise comparisons with controls, the gene expression of TOLLIP was significantly decreased in untreated (P = 0.02) but not in treated celiacs (P = 0.75). Transcripts of TLR3, TLR4, TLR5, and single immunoglobulin IL-1R–related molecule were also found in the small intestinal biopsies, but their expressions were comparable among untreated celiacs, treated celiacs, and controls (data not shown).
By analyzing gene expression profiles in small intestinal biopsies in celiac disease, we have found IL-8 to be a solid indicator of intestinal inflammation and altered expressions of TLR2, TLR9, and TOLLIP as suggestive of the importance of microbiota-associated factors in the development of celiac disease, although we could not find any differences in the small intestinal microbiota by the methods used in the study.
Previous studies evaluating fecal and gut microbiota in celiac patients have yielded partly conflicting results. Although increased bacterial diversity and changes in several bacterial groups in the microbiota of Spanish and Italian pediatric patients with celiac disease have been reported in various studies (5–6,8–11), a Swedish study failed to show microbiota difference between children with and without celiac disease (7); however, small intestinal biopsies from children with celiac disease born during the Swedish celiac disease epidemic in the late 1980s and early 1990s were enriched with rod-shaped bacteria, suggesting that early dietary patterns may play an important role in both the development of celiac disease and small intestinal colonization (7). Correspondingly, a Spanish study found that early milk-feeding practices influence early gut colonization process in infants at risk for celiac disease (26); however, it remains to be elucidated whether differences in early dietary patterns or some other factors may explain the above-mentioned discrepancy between our study, the Swedish study, and those conducted in Southern Europe.
Expression of TLRs in the small intestinal biopsies in patients with celiac disease has been variable in previous studies. Szebeni et al (27) found increased expressions of TLR2 and TLR4 in untreated and treated celiacs as compared with controls at both mRNA and protein levels. A Finnish study without a group of treated celiacs demonstrated a decreased gene expression of TLR2 and higher densities of TLR4-positive cells by immunohistochemistry in untreated celiacs in comparison with controls (28). A study, again lacking a group of treated celiacs, showed increased expression of TLR2 mRNA only in gluten-sensitive patients but not in patients with celiac disease (29). Our finding of decreased gene expression of TLR2 in untreated celiacs is in accordance with the above-mentioned Finnish study (28). It is noteworthy that exactly the same probe and primers for TLR2 analysis were used in these 2 studies. Discrepancies of our findings with other studies are probably the result of differences in patient selection and methods.
We found that TOLLIP mRNA was decreased in untreated but not in treated celiacs. To our knowledge, the altered gene expression of TOLLIP has not been described in patients with celiac disease. TOLLIP is an intracellular protein that inhibits TLR signaling (12). Overexpression of TOLLIP in intestinal epithelial cells in vitro has been shown to inhibit TLR activation after stimulation with lipopolysaccharide or lipotechoic acid, a phenomenon termed lipopolysaccharide tolerance (30). Intestinal epithelial cells from patients with inflammatory bowel disease have been demonstrated to fail to upregulate TOLLIP expression that may boost chronic inflammation (31). Our finding of the decreased expression of TOLLIP transcript in untreated celiacs suggests that a loss of tolerance to gut microbiota may be a contributory factor in gluten-driven inflammation in celiac disease.
We demonstrated for the first time increased gene expression of TLR9 in the small intestinal mucosa in untreated celiacs. TLR9 recognizes unmethylated 2′-deoxyribo (cytidine-phosphate-guanine) dinucleotides, which are found with 20-fold greater frequency in bacterial DNA than in mammalian DNA (12). A previous experimental study described a significant protective role of TLR9 activation with cytidine-phosphate-guanine DNA in necrotizing enterocolitis (32), suggesting that TLR9 signaling may have anti-inflammatory properties in the intestine. Therefore, our finding of increased expression of the TLR9 gene in the inflamed small intestine of untreated celiacs is unexpected and suggests either another function of the TLR9 gene or a defect in the downstream signaling of the gene in these patients.
Concerning the increased IL-8 mRNA response in the small intestine in untreated celiacs, we propose a scenario in which gluten acts as a trigger. Gliadin, a complex glycoprotein present in gluten-containing grains, exists in 3 variants: α-, γ-, and ω-gliadin, the first being most prevalent. α-Gliadin is a multifunctional protein that contains multiple motifs, which accounts for its reported cytotoxic, immunogenic, and intestinal permeability effects via different peptides (reviewed in (33)). A 17-mer peptide responsible for the chemokine receptor CXCR3-dependent production of IL-8 in celiac disease was discovered (13). Gluten was able to induce greater IL-8 production in peripheral blood mononuclear cells from patients with celiac disease than from healthy controls. Interestingly, CXCR3 antibody was able to block the gluten-induced IL-8 production in patients with celiac disease but not in healthy controls, indicating that IL-8 production is differently regulated in these 2 groups (13). Intestinal mucosal expression of the chemokine receptor CXCR3, located in both intestinal epithelia and lamina propria, has been shown to be upregulated in untreated celiac disease (34). The receptor CXCR3 was also involved in the gliadin-induced increase in intestinal permeability and zonulin release (34). Serum IL-8 concentrations, which correlate significantly with tissue transglutaminase immunoglobulin A titers (35), have been demonstrated to be elevated in both untreated celiac disease and dermatitis herpetiformis (35,36). In accordance with our original finding in celiac disease reported in the present study, the gene expression of IL-8 in small intestinal biopsies in dermatitis herpetiformis normalized after implementation of a gluten-free diet, suggesting gluten-induced IL-8 production in small intestinal mucosa as a principal source of serum IL-8 (36). Until now, it was not known whether IL-8 production both in small intestinal mucosa and in peripheral blood mononuclear cells was regulated in a similar manner in patients with celiac disease.
Our findings about altered gene expression profiles of TLRs and an inhibitor of their signaling in celiac disease suggest that microbiota-associated factors are important in the pathogenesis of the disease. A more detailed assessment of mucosal microbiota would be needed. To explore the issue more closely and the role and mechanisms of IL-8 production in small intestinal mucosa in celiac disease warrants further study.
Ms Riikka Lankinen is acknowledged for excellent laboratory assistance.
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Keywords:Copyright 2012 by ESPGHAN and NASPGHAN
celiac disease; interleukin-8; microbiota; Toll-interacting protein; Toll-like receptors