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      Point Mutations in FimH Adhesin of Crohn's Disease-Associated Adherent-Invasive Escherichia coli Enhance Intestinal Inflammatory Response

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          Abstract

          Adherent-invasive Escherichia coli (AIEC) are abnormally predominant on Crohn's disease (CD) ileal mucosa. AIEC reference strain LF82 adheres to ileal enterocytes via the common type 1 pili adhesin FimH and recognizes CEACAM6 receptors abnormally expressed on CD ileal epithelial cells. The fimH genes of 45 AIEC and 47 non-AIEC strains were sequenced. The phylogenetic tree based on fimH DNA sequences indicated that AIEC strains predominantly express FimH with amino acid mutations of a recent evolutionary origin - a typical signature of pathoadaptive changes of bacterial pathogens. Point mutations in FimH, some of a unique AIEC-associated nature, confer AIEC bacteria a significantly higher ability to adhere to CEACAM-expressing T84 intestinal epithelial cells. Moreover, in the LF82 strain, the replacement of fimH LF82 (expressing FimH with an AIEC-associated mutation) with fimH K12 (expressing FimH of commensal E. coli K12) decreased the ability of bacteria to persist and to induce severe colitis and gut inflammation in infected CEABAC10 transgenic mice expressing human CEACAM receptors. Our results highlight a mechanism of AIEC virulence evolution that involves selection of amino acid mutations in the common bacterial traits, such as FimH protein, and leads to the development of chronic inflammatory bowel disease (IBD) in a genetically susceptible host. The analysis of fimH SNPs may be a useful method to predict the potential virulence of E. coli isolated from IBD patients for diagnostic or epidemiological studies and to identify new strategies for therapeutic intervention to block the interaction between AIEC and gut mucosa in the early stages of IBD.

          Author Summary

          The etiology of inflammatory bowel diseases, in particular Crohn's disease (CD), involves disorders in host genetic factors and intestinal microbiota. Adherent-invasive Escherichia coli (AIEC) are receiving increasing attention because they have been reported worldwide to be more prevalent in CD patients than in healthy subjects. AIEC adhere to ileal enterocytes via type 1 pili, which recognize the CEACAM6 receptor, which is abnormally expressed in CD patients. The ability of AIEC to adhere to intestinal epithelial cells expressing CEACAM6 could be correlated with the presence of amino acid substitutions in the type 1 pili FimH adhesin subunit. AIEC strains express FimH protein variants with recently acquired amino acid mutations, which is a typical signature of pathoadaptive evolution of bacterial pathogens. AIEC-associated mutations in FimH confer on AIEC bacteria a significantly higher ability to adhere to CEACAM-expressing intestinal epithelial cells. Our results highlight a mechanism of AIEC pathogenic evolution that involves selection of FimH pathoadaptive mutations, which are required for AIEC gut colonization, which leads to the development of chronic inflammation in a genetically susceptible host. The analysis of fimH SNPs may be a useful method to predict the potential virulence of E. coli isolated from IBD patients in epidemiological studies and to develop new therapeutic interventions.

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          Salmonella enterica Serovar Typhimurium Exploits Inflammation to Compete with the Intestinal Microbiota

          Introduction The evolution of pathogenic microorganisms has been shaped to a great extent by their interaction with cognate host species. Colonization is the first step of any infection. For enteropathogenic bacteria, this poses a formidable task as the target host organ is already colonized by a dense microbial community, the microflora, or “microbiota”. Intestinal colonization by microbiota begins immediately after birth and lasts for life. In a healthy intestine, the microbiota is quite stable, and its gross composition at higher taxonomic levels is similar between individuals, and even between humans and mice [1]. The intestinal ecosystem is shaped by symbiotic interactions between the host and the microbiota. Microbiota composition is influenced by nutrient availability, local pH, and possibly also by the host's immune system [2]. Conversely, the microbiota optimizes nutrient utilization [3,4], and boosts maturation of intestinal tissues and the intestinal immune system [5–7]. In addition, the microbiota provides an efficient barrier against infections (“colonization resistance”), which must be overcome by enteropathogenic bacteria. It is poorly understood how enteropathogens can achieve that task. Here, we used Salmonella enterica subspecies 1 serovar Typhimurium (S. Tm) and a mouse colitis model to study strategies by which enteropathogenic bacteria break colonization resistance. S. Tm infects a broad range of animal species and is a frequent cause of intestinal infections in the human population. The normal murine microbiota provides colonization resistance and prevents intestinal colonization upon oral S. Tm infection. Oral treatment with the antibiotic streptomycin (20 mg of streptomycin intragastric [i.g.]) transiently reduces the microbiota by >80% and disrupts colonization resistance for a period of 24 h [8,9]. The residual microbiota re-grows within 2–3 d, and colonization resistance is re-established ([9]; unpublished data). These studies have provided the basis for a “streptomycin mouse model” for Salmonella enterocolitis [10]: 1 d after streptomycin treatment, oral infection with S. Tm leads to efficient colonization of the murine intestine, especially the cecum and the colon (approximately 109 colony-forming units [CFU]/gram; Figures 1A and S1) [8,9,11]. Wild-type S. Tm (S. Tmwt) triggers pronounced intestinal inflammation (colitis) and colonizes the intestinal lumen at high densities over extended periods of time [8,10–12]. This “streptomycin mouse model” can be used to study bacterial virulence factors required for colonization and triggering of intestinal inflammation. For example, S. Tm strains lacking the two virulence-associated type III secretion systems (e.g., S. Tm ΔinvG sseD::aphT [S. Tmavir] [13]) cannot trigger colitis. In addition, these mutants were found to colonize the murine intestine only transiently [11,13]. The reason for this colonization defect has remained elusive. Figure 1 Microbiota Outcompete S. Tmavir but not S. Tmwt (A) Streptomycin-treated mouse model. The antibiotic transiently reduces the microbiota (grey circles) in the lumen of the large intestine, reduces colonization resistance, and allows colonization and induction of colitis by S. Tmwt. (B) Streptomycin-treated C57BL/6 mice (n = 7 per group) were infected with S. Tmavir (blue) or S. Tmwt (red; 5 × 107 CFU i.g.). At indicated time points mice were sacrificed, S. Tm loads were determined in cecal content, mLN, and spleen, and cecal pathology was scored. Detection limits (dotted lines): cecal content, 10 CFU/g; mLN, 10 CFU/organ; spleen, 20 CFU/organ. *, p ≤ 0.05; statistically significant difference between S. Tmavir and S. Tmwt. Boxes indicate 25th and 75th percentiles, black bars indicate medians, and whiskers indicate data ranges. (C–H) Representative confocal fluorescence microscopy images of cecum tissue sections from the mice shown in (B). Nuclei and bacterial DNA are stained by Sytox green (green), the epithelial brush border actin by Alexa-647-phalloidin (blue), and extracellular S. Tm in the intestinal lumen by anti–S. Tm LPS antiserum (red). Normal microbiota in unmanipulated mice (C), microbiota 1 d after streptomycin (sm) treatment (D), streptomycin-treated mice infected for 1 or 4 d with S. Tmavir or S. Tmwt (E–H). The S. Tm colonization levels are indicated (CFU/g); L, cecum lumen. To explore this, we analyzed microbiota compostition in S. Tmwt– and S. Tmavir–infected mice and the role of inflammation for Salmonella colonization and competition against the intrinsic microbiota. We found that inflammation shifts the balance between the protective microbiota and the pathogen S. Tm in favour of the pathogen. This principle might apply to various other pathogens and therefore constitute a novel paradigm in infectious biology. Results S. Tmavir but Not S. Tmwt Is Outcompeted by Commensal Microbiota First, we confirmed the differential colonization efficiency of S. Tmwt and S. Tmavir in the streptomycin mouse model. Unlike S. Tmwt, intestinal S. Tmavir colonization levels decreased significantly by day 4 post-infection (p.i.) in a highly reproducible fashion (Figure 1B). This coincided with re-growth of the microbiota as revealed by immunofluorescence microscopy (Figure 1C–1H). By anaerobic culture, DNA isolation, and 16S rRNA gene sequencing, high densities of characteristic members of the intestinal microbiota (Clostridium spp., Bacteroides spp., and Lactobacillus spp. [14]) were found in S. Tmavir–infected, but not in S. Tmwt–infected, animals at day 4 p.i. (Table 1). Both the S. Tm/microbiota ratio and the composition of the microbiota itself differed between mice infected with S. Tmavir and S. Tmwt. These data demonstrated that residual microbiota surviving the streptomycin treatment can re-grow, outcompete S. Tmavir, and thereby re-establish colonization resistance. In contrast, S. Tmwt can suppress re-growth of the residual microbiota. Therefore, the streptomycin mouse model allows study of the principal mechanisms by which enteropathogens manipulate the intestinal ecosystem. Table 1 Bacterial Genera Recovered by Anaerobic Culture from S. Tm Infected Mice S. Tmwt Alters Composition of the Microbiota in the Streptomycin Mouse Model To better characterize the effect of S. Tm on microbiota composition, we employed 16S rRNA gene sequencing (see Materials and Methods). This method allows a quantitative comparison of microbial communities, including bacterial species that cannot be cultivated in vitro. The analysis comprised five different groups of mice and addressed the effect of the streptomycin pretreatment per se as well as the effect of S. Tmavir and S. Tmwt infection on microbiota composition (Figure 2). Figure 2 16S rRNA Gene Sequence Analysis of Microbiota Manipulation by S. Tmwt and S. Tmavir in the Streptomycin Mouse Model Cecal contents were recovered from unmanipulated mice, mice at days 1 or 5 after streptomycin treatment (20 mg i.g.), and streptomycin-treated mice 4 d after infection with S. Tmavir and S. Tmwt (5 × 107 CFU i.g.; all n = 5). Total DNA was extracted, and bacterial 16S rRNA genes were PCR-amplified using universal bacterial primers, cloned, and sequenced (approximately 100 sequences per animal; five animals per group; see Materials and Methods). (A) Pie diagrams showing the microbiota composition at the phylum level. Numbers below the diagrams indicate bacteria/gram cecal content as defined by Sytox green staining. *The lower bacterial density in S. Tmwt–infected mice is attributable to a high proportion of cellular debris in the intestinal lumen (see Figure 1G). #In these groups no Salmonella 16S rRNA genes were identified. ‡Proteobacterial sequences belonged to Salmonella (E. coli) in the following percentages: 91 (1), 15 (70), 87 (11), 55 (38), and 100 (0). See also Table S1. (B) Visual depiction of the microbiota composition of individual mice. The animals were grouped based on the similarity of their microbiota composition at the phylum level (using the Canberra distance as metric). The resulting groupings are depicted as a dendrogram, and observed phylum counts for each mouse are shown as a heat map (0%–100% of all identified 16S rRNA gene sequences). Labels indicate unique mouse identifier numbers. The experimental groups are indicated. p.sm., post–streptomycin treatment. In line with published data, a large fraction of the murine microbiota in unmanipulated mice belonged to either the Firmicutes (including Clostridium spp. and Lactobacillus spp.; 39% ± 10%) or the Bacteroidales (53% ± 13%; Figure 2) [1,15–17]. Streptomycin treatment reduced the global density of the microbiota by approximately 90% (Figure 2; see also Figure 1C and 1D) and changed its relative composition (Figure 2A and 2B; Table 2). The composition of the remaining microbiota varied substantially between individual members of this group (Figure 2B). Most likely, this is attributable to the unstable situation created by the antibiotic and may arise from slight animal-to-animal variations in the timing or speed of the gut passage of the antibiotic and/or from species-specific differences in antibiotic susceptibility and rate of re-growth. Table 2 Phylum-Level Comparison of Microbiota in Streptomycin-Treated S. Tm–Infected Mice from Experiment Described in Figure 2 Five days after the antibiotic treatment, the microbiota had re-grown to normal density and microbiota composition, at least at the phylum level (Figure 2A and 2B; Table 2; p = 0.35078). Infection with S. Tmavir did not interfere detectably with re-growth of the normal microbiota in the streptomycin-pretreated mouse model (Figure 2B; Table 2). In contrast, S. Tmwt significantly altered the cecal microbiota composition (Figure 2A and 2B; Table 2; p 90% of all sequences, and Salmonella spp. generally represented the most prominent (up to 100%) proteobacterial species in the S. Tmwt–infected animals. These observations were confirmed by fluorescence in situ hybridization (FISH) of fixed cecal content (Figure S2). This demonstrates that S. Tmwt interferes with microbiota re-growth and represents the predominant species at day 4 p.i. It should be noted that other proteobacterial species (e.g., Escherichia coli) were also present in significant numbers in the cecum of most S. Tmwt–infected animals (Figure 2A). These proteobacterial strains are low abundance members of the normal gut microbiota of our mouse colony ( 10 different commensal species, including commensal E. coli strains from our mouse colony, grown in vitro (all negative). DNA was stained with Sytox green (0.1 μg/ml; Sigma-Aldrich, http://www.sigmaaldrich.com/) and F-Actin with Alexa-647-phalloidin (Molecular Probes, http://probes.invitrogen.com/). Sections were mounted with Vectashield hard set (Vector Laboratories, http://www.vectorlabs.com/) and sealed with nail polish. Images were recorded using a PerkinElmer (http://www.perkinelmer.com/) Ultraview confocal imaging system and a Zeiss (http://www.zeiss.com/) Axiovert 200 microscope. For quantification of total bacterial numbers, cecal contents were weighed, fixed in 4% paraformaldehyde, and stained with Sytox green (0.1 μg/ml). Bacteria were counted in a Neubauer's counting chamber using an upright fluorescence microscope (Zeiss). Broad-range bacterial 16S rRNA gene sequence analysis. Total DNA was extracted from cecal contents using a QIAmp DNA stool mini kit (Qiagen, http://www1.qiagen.com/) and a Tissuelyzer device (Qiagen). 16S rRNA genes were amplified by PCR using primers Bact-7F (5′-AGA GTT TGA TYM TGG CTC AG-3′) and Bact-1510R (5′-ACG GYT ACC TTG TTA CGA CTT-3′) and the following cycling conditions: 95 °C, 5 min; 22 cycles of 95 °C, 30 s; 58 °C, 30 s; 72 °C, 2 min; followed by 72 °C, 8 min; 4 °C, ∞. Reaction conditions (100 μl) were as follows: 50 mM KCl, 10 mM Tris-HCl (pH 8.3), 1.5 mM Mg2+, 0.2 mM dNTPs, 40 pmol of each primer, and 5 U of Taq DNA polymerase (Eppendorf, http://www.eppendorf.com/). Fragments were purified by gel electrophoresis, excised, recovered using the gene clean kit (Qbiogene; http://www.qbiogene.com/) and dried. The PCR products were suspended in 10 μl of sterile distilled water and between 2 and 5 μl was ligated into pGEM-T Easy Vectors (Promega, http://www.promega.com/). The ligated vectors were transformed into high-efficiency competent JM109 E. coli cells (Promega), plated on LB-carbenicillin agar, and subjected to blue-white screening of colonies. White colonies were picked into 96-well boxes containing 500 μl of Circlegrow medium (Qbiogene, http://www.qbiogene.com/) per well and grown overnight at 37 °C, and the plasmid DNA was then prepped using a modified semi-automated alkaline lysis method. Sequencing was carried out using Applied Biosystems (http://www.appliedbiosystems.com/) BigDye terminators (version 3.1) and run on Applied Biosystems 3730 sequencers. The 16S rRNA gene inserts were sequenced using two primers targeted towards the vector end sequences, M13r (5′-CAGGAAACAGCTATGACC-3′) and T7f (5′-TAATACGACTCACTATAGGG-3′), and one towards an internal region of the gene, 926r (5′-CCGTCAATTC[A/C]TTT[A/G]AGT-3′), in order to bridge any gaps between the sequences generated from the two end primers. Contigs were built from each three-primer set of sequences using the GAP4 software package [51] and converted to “sense” orientation using OrientationChecker software [52]. These files were then aligned using MUSCLE [53], and the alignments were manually inspected and corrected using the sequence editor function in the ARB package [54]. The files were then tested for the presence of chimeric sequences using Mallard [52] and Bellerophon [55], and putative chimeras were checked using Pintail [56] and BLAST [57]. Positively identified chimeras were removed, and the remaining sequences were examined with the Classifier function at the Ribosomal Database Project II Web site [48] in order to give a broad classification at the phylum level. To obtain more detailed taxonomic information the sequences were divided into phylotypes by generating distance matrices in ARB (with Olsen correction), which were then entered into the DOTUR program [58] set to the furthest neighbour and 99% similarity settings. The resulting phylotypes were then assigned similarities to nearest neighbours using BLAST. Statistical analysis of bacterial colonization and intestinal pathology. Statistical analyses of viable CFU and pathological scores were performed using the exact Mann-Whitney U Test and the SPSS version 14.0 software, as described before [8]. Values of p < 0.05 were considered statistically significant. Box-plots were created using GraphPad Prism 4 version 4.03 (GraphPad Software, http://www.graphpad.com/). Statistical analysis of microbiota composition. Differences in the phylogenetic compositions of samples were assessed by first assigning the detected 16S rRNA gene sequences to their respective phyla, and then computing the normalized Euclidean distance between the phyla counts. The observed differences were judged for their statistical significance by performing Monte Carlo randomizations: 16S rRNA gene sequences were shuffled between two samples, such that overall sample sizes and total counts for each phylum were maintained. Euclidean distances were then re-computed, and the fraction of distances larger than or equal to the observed distances determined the p-values. Bonferroni correction for multiple testing means that p-values below 0.005 indicate statistical significance in Figures 2 and 6 and Table 2. Supporting Information Figure S1 Colitis Score Developed for the Streptomycin-Pretreated Mouse Model for Salmonella Colitis [8] Mice were pretreated with a single dose of streptomycin (20 mg i.g.) and 24 h later infected with 5 × 107 CFU of S. Tmavir (A) or S. Tmwt i.g. (B). Mice were sacrificed 1 d p.i. Left panels of (A) and (B): macroscopic appearance of the cecum from S. Tmavir– and S. Tmwt–infected mice, respectively. Note the reduction in size and purulent cecal content in case of S. Tmwt–induced colitis. Middle panels: HE-stained cross-section of ceca shown in left panel (scale bar: 1 mm). Note the submucosal edema (se), which is a characteristic of S. Tmwt–induced colitis. L, cecal lumen. Right panels: at higher magnification, large numbers of goblet cells (gc) are observed in the cecal mucosa of healthy mice. Colitis leads to reduced numbers of goblet cells due to pronounced epithelial regeneration. Note infiltrating polymorphonuclear leukocytes and desquamated epithelium in the S. Tmwt–infected cecum (scale bar: 0.05 mm). Detailed parameters for colitis score are listed in table at bottom of figure. (272 KB PDF) Click here for additional data file. Figure S2 FISH Analysis of Microbiota Manipulation by S. Tmwt and S. Tmavir in the Streptomycin Mouse Model Cecal contents were fixed in PBS (4% paraformaldehyde [pH 7.4]; 4 °C; 12 h), washed in PBS, applied onto polylysine-coated slides, and air-dried. Bacteria were permeabilized (70.000 U/ml of lysozyme; 5 mM EDTA; 100 mM Tris/HCl [pH 7.5]; 37 °C; 10 min), dehydrated with ethanol, and hybridized with HPLC-purified, 5′-labelled 16S rRNA probes (5% formamide, 90 mM NaCl, 20 mM Tris/HCl [pH 7.5]; 46 °C; 2 h): Eub338-cy5 (5′-GCT GCC TCC CGT AGG AGT-3′; detection of all eubacteria [59]), LGC-cy3 or LGC-fluorescein (5′-TCA CGC GGC GTT GCT C-3′; detection of gram-positive bacteria with low G+C content; Firmicutes [60]), and Bac303-cy3 or Bac303-fluorescein (5′-CCA ATG TGG GGG ACC TT-3′; detection of the Bacteroidales group of the Bacteroidetes [61]). Slides were washed at 48 °C (636 mM NaCl, 5 mM EDTA, 0.01% SDS, 20 mM Tris/HCl [pH 7.5]) as described [59]. S. Tm was detected by immunostaining (see above), and FISH detection was performed using the Eub338-cy5 probe. The relative abundance of Firmicutes, Bacteroidales, and S. Tm was determined by co-staining and imaging at 630× magnification using a PerkinElmer Ultraview confocal imaging system and a Zeiss Axiovert 200 microscope. For each condition, 500–1,750 bacteria were evaluated. FISH analysis of cecal microbiota from the mice shown in Figure 2. Cecal contents from unmanipulated mice, from mice at days 1 or 5 after streptomycin treatment (20 mg, i.g.), and from streptomycin-treated mice 4 d after infection with S. Tmavir and S. Tmwt (5 × 107 CFU i.g.; all n = 5) were recovered, fixed on cover slips, and hybridized with Eub338 (all bacteria). Firmicutes and Bacteroidales were recognized by hybridization with LGC and BAC303 probes, respectively, and S. Tm by an anti–S. Tm LPS antiserum (see Materials and Methods). Firmicutes (green), Eub338+ Bac303− LGC+; Bacteroidales (yellow), Eub338+ Bac303+ LGC−; Salmonella (red with white stripes), Eub338+ LPS+; “unknown” (grey), Eub338+ LGC− Bac303− LPS−. Abundance of respective groups is expressed as percentage of total Eub338+ bacteria. The results of the FISH analysis confirmed the results obtained via 16S rRNA gene sequencing (Figure 2). Slight differences in the percent composition of the microbiota with respect to Firmicutes, Bacteroidales, and Salmonella spp. obtained via both methods are attributable to species-specific differences in lysis efficiency and 16S rRNA gene copy number. (124 KB PDF) Click here for additional data file. Figure S3 Cecal Histopathology in Acute and Chronic Mouse Colitis Models Shown in Figures 4 and 5 Frozen sections of cecal tissues (5 μm) were stained with HE (scale bar: 200 μm). Acute Salmonella colitis was observed in C57BL/6 mice infected with S. Tmwt (A) but not with S. Tmavir (B) 4 d p.i. (compare with Figure 3A). Chronic Salmonella colitis was observed in 129Sv/Ev mice infected with S. Tmwt (C) but not with S. Tmavir (D) 47 d p.i. (compare with Figure 3B). Genetic predisposition (lack of anti-inflammatory cytokine IL10) leads to sporadic occurrence of colitis in C57/BL6IL10−/− mice (E). However, some C57/BL6IL10−/− mice are not affected (F) (compare with Figure 3C). A large number of C3H/HeJBirIL10−/− mice were affected by cecal inflammation (G), but one was not (H) (compare with Figure 3C). L, cecal lumen; se, submucosal edema. (735 KB PDF) Click here for additional data file. Figure S4 Colitis Scores for C57/BL6IL10−/− and C3H/HeJBirIL10−/− Mice (A) Frozen sections of cecal tissues (5 μm) were stained with HE (scale bar: 200 μm). Histopathology was scored with respect to submucosal edema (black), polymorphonuclear leukocyte infiltration (grey), loss of goblet cells (dark grey), and epithelial destruction (light grey). The scoring scheme is shown in Figure S1. Scores are plotted as stacked vertical bars. One animal was sacrificed at the end of day 1 p.i. for humane reasons (marked with †). (B) Confocal fluorescence microscopy image of cecal lumen reveals normal high microbiota densities. Upper left: C3H/HeJBirIL10−/− animal marked with ‡ in (A). The remaining images show animals described in Figure 6B. Upper right: VILLIN-HA control, S. Tmavir infected. Lower left: VILLIN-HA+CL4-CD8 (inflammation), non-infected. Lower-right: VILLIN-HA+CL4-CD8 (inflammation), S. Tmavir infected. Bacterial DNA is stained by Sytox green (green) and extracellular S. Tm by anti-S. Tm LPS antiserum (red). Scale bar: 20 or 50 μm as specified. (1.8 MB PDF) Click here for additional data file. Figure S5 S. Tmavir Efficiently Colonizes Germ-Free Mice Germ-free C57BL/6 mice (n = 8) were infected with S. Tmavir (5 × 107 CFU i.g.) and sacrificed at day 2 or 4 p.i. (open blue boxes). For comparison, previous data [62] from five mice infected for 1 d with S. Tmwt are included (open red boxes). S. Tm colonization was analyzed in the cecum content (day 2 p.i.), and cecum pathology was scored (see Material and Methods). Detection limits (dotted line): cecum, 10 CFU/g; mLN, 10 CFU/organ; spleen, 20 CFU/organ. At day 4 p.i., S. Tmavir colonization levels in germ-free mice in the absence of re-growing microbiota were significantly higher when compared to streptomycin-treated SPF mice (p = 0.002; compare with Figure 3A, left panel). (105 KB PDF) Click here for additional data file. Figure S6 16S rRNA Gene Sequence Analysis of Microbiota in VILLIN-HACL4-CD8 Model Visual depiction of the microbiota composition of individual mice. The animals were grouped based on the similarity of their microbiota composition at the phylum level (using the Canberra distance as metric). The resulting groupings are depicted as a dendrogram, and observed phylum counts for each mouse are shown as a heat map (0%–100% of all identified 16S rRNA gene sequences). Labels give unique mouse identifier numbers. The experimental groups are indicated. (64 KB PDF) Click here for additional data file. Table S1 Broad-Range Bacterial 16S rRNA Gene Sequence Analysis of the Microbiota Composition from the Experiment Shown in Figures 2 and 6 (277 KB XLS) Click here for additional data file. Table S2 Phylum-Level Comparison of Microbiota of VILLIN-HACL4-CD8 Model from the Experiment Described in Figure 6 (35 KB DOC) Click here for additional data file. Accession Numbers The GenBank (http://www.ncbi.nlm.nih.gov/Genbank/) accession numbers for the 16S RNA gene sequences shown in Figure 2 are EF604903–EF605247, and for those shown in Figure 6C are EF604904–EF605247 and EU006095–EU006496.
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            Enhanced Escherichia coli adherence and invasion in Crohn's disease and colon cancer.

            Altered mucosal glycosylation in inflammatory bowel disease and colon cancer could affect mucosal bacterial adherence. This study aimed to quantify and characterize mucosa-associated and intramucosal bacteria, particularly Escherichia coli, in these conditions. Mucosa-associated bacteria were isolated, after dithiothreitol mucolysis, from biopsy samples obtained at colonoscopy (Crohn's disease, n = 14 patients; ulcerative colitis, n = 21; noninflamed controls, n = 24) and at surgical resection (colon cancer, n = 21). Intramucosal bacteria were grown after gentamicin treatment followed by hypotonic lysis. Mucosa-associated and intramucosal bacteria were cultured more commonly in Crohn's disease (79%, P = 0.03; and 71%, P < 0.01, respectively), but not ulcerative colitis (38% and 48%), than in noninflamed controls (42% and 29%) and were commonly cultured from colon cancers (71% and 57%). Mucosa-associated E. coli, which accounted for 53% of isolates, were more common in Crohn's disease (6/14; 43%) than in noninflamed controls (4/24, 17%), as also were intramucosal E. coli: Crohn's disease, 29%; controls, 9%. E. coli expressed hemagglutinins in 39% of Crohn's cases and 38% of cancers but only 4% of controls, and this correlated (P = 0.01) with adherence to the I407 and HT29 cell lines. Invasion was cell-line dependent. E. coli, including nonadherent isolates, induced interleukin-8 release from the cell lines. E. coli adhesins showed no blood group specificity, excepting 1 cancer isolate (HM44) with specificity for the Thomsen-Friedenreich antigen, but they could be blocked by soluble plantain fiber. These studies support a central role for mucosally adherent bacteria in the pathogenesis of Crohn's disease and colon cancer. Soluble plant fibers that inhibit their adherence have therapeutic potential.
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              CEACAM6 acts as a receptor for adherent-invasive E. coli, supporting ileal mucosa colonization in Crohn disease.

              The ileal mucosa of Crohn disease (CD) patients is abnormally colonized by adherent-invasive E. coli (AIEC) that are able to adhere to and invade intestinal epithelial cells. Here, we show that CD-associated AIEC strains adhere to the brush border of primary ileal enterocytes isolated from CD patients but not controls without inflammatory bowel disease. AIEC adhesion is dependent on type 1 pili expression on the bacterial surface and on carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) expression on the apical surface of ileal epithelial cells. We report also that CEACAM6 acts as a receptor for AIEC adhesion and is abnormally expressed by ileal epithelial cells in CD patients. In addition, our in vitro studies show that there is increased CEACAM6 expression in cultured intestinal epithelial cells after IFN-gamma or TNF-alpha stimulation and after infection with AIEC bacteria, indicating that AIEC can promote its own colonization in CD patients.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                January 2013
                January 2013
                24 January 2013
                : 9
                : 1
                : e1003141
                Affiliations
                [1 ]M2iSH, UMR1071 Inserm, Université d'Auvergne, USC-INRA 2018, Clermont-Ferrand, France
                [2 ]Institute of Hygiene, University Hospital Münster, Münster, Germany
                [3 ]University of Washington School of Medicine, Department of Microbiology, Seattle, Washington, United States of America
                [4 ]Inserm U995, Université Lille II, Hôpital Claude Huriez, Lille, France
                [5 ]Service de Bactériologie, CHU, Clermont-Ferrand, France
                [6 ]Institut Universitaire de Technologie, Génie Biologique, Aubière, France
                University of Utah, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ND AM ADM NB. Performed the experiments: ND JD MMM MB SC DK. Analyzed the data: ND ES RB ADM NB. Contributed reagents/materials/analysis tools: ES RB CN JFC CGR. Wrote the paper: ND JD ES ADM NB.

                Article
                PPATHOGENS-D-12-01154
                10.1371/journal.ppat.1003141
                3554634
                23358328
                ba80ac48-9f2f-4cd1-acbe-ccd79b35e5e2
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 May 2012
                : 4 December 2012
                Page count
                Pages: 17
                Funding
                This study was supported by INSERM (UMR1071), INRA (USC-2018) and by grants from the Association F. Aupetit (AFA), European Commission through FP7 IBDase project and from ANR in the frame of ERA-NET PathoGenomics and by the ERA-NET PathoGenomics no. 0315443. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Microbiology

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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