Skip to main content
NCBI home page
Immunology logoLink to Immunology
. 2012 Jul;136(3):312–324. doi: 10.1111/j.1365-2567.2012.03581.x

Differential intestinal M-cell gene expression response to gut commensals

Susan Lapthorne 1,*, John MacSharry 1,*, Paul Scully 1, Kenneth Nally 1,†, Fergus Shanahan 1,†
PMCID: PMC3385031  PMID: 22385384

Abstract

Different rates of bacterial translocation across the gut mucosa have been reported but few studies have examined translocation of commensals at the level of the gut epithelial microfold (M) cell. We used an in vitro M-cell model to quantify translocation and determine the transcriptional response of M cells to various commensal bacteria. The transport kinetics and gene expression profile of M cells in response to different bacterial strains, namely Lactobacillus salivarius, Escherichia coli and Bacteroides fragilis, was assessed. Bacterial strains translocated across M cells with different efficiencies; E. coli and B. fragilis translocated with equal efficiency whereas L. salivarius translocated with less efficiency. Microarray analysis of the M cell response showed both common and differential gene expression changes between the bacterial strains. In the presence of bacteria, but not control beads, up-regulated genes were mainly involved in transcription regulation whereas pro-inflammatory and stress response genes were primarily up-regulated by E. coli and B. fragilis, but not L. salivarius nor beads. Translocation of bacteria and M-cell gene expression responses were confirmed in murine M cells following bacterial challenge in vivo. These results demonstrate that M cells have the ability to discriminate between different commensal bacteria and modify subsequent immune responses.

Keywords: commensal bacteria, immune response, microfold cell, microarray, translocation

Introduction

The gastrointestinal tract is home to an ecosystem that has the highest recorded microbial density.1 Although protected by immunological and non-immunological defences and often referred to as a functional mucosal ‘barrier’, the surface of the gut is actually designed not only for uptake of nutrients but also for exchange of signals to and from the lumen. A single layer of epithelium spanning a huge surface area separates the internal milieu from the external environment.

Host–microbe interactions within the gut are essential for digestive and immune development and for maintenance of mucosal homeostasis.2 An essential feature of these interactions involves immunosensory interpretation of the luminal microenvironment and this includes ‘sampling’. Sampling of the luminal contents is the controlled active process of transportation of microbial products and antigens by host haematopoietic and epithelial cells.3 The gut contents are mainly sampled at sites where specialized epithelial or microfold (M) cells overlie lymphoid follicles, aggregates of which comprise Peyer’s patches. M cells transport material from the lumen to the underlying immune cells where processing and antigen presentation occur; thereby, initiating effector and regulatory immune responses.3–6 Much attention has been focused on receptors and recognition structures deployed for M-cell-mediated uptake of pathogens,7 but discriminatory processes for uptake of different commensals are less well studied.8

Translocation refers to the passage of bacteria from the lumen to the mesenteric lymph nodes and other extraintestinal organs.9 Traditionally, this has been based upon detection of enteric bacteria by culture-based methods in the mesenteric lymph node. Using this approach, differential rates of bacterial translocation have been reported in vivo in murine systems,9 but the factors underlying the differences and whether the differential arises, in part, at the level of the M cell or at a subsequent stage in the process, are not well understood. In addition, it is unclear if the M cell has the capacity for immunosensory discriminatory responses beyond uptake and translocation in relation to commensals. To investigate these questions, we used a well-described in vitro model of M-cell function to examine differential bacterial translocation and to determine whether different commensal bacteria elicit the same or distinct patterns of gene expression within the M cell.10,11 Three different commensal bacterial strains from humans (Lactobacillus salivarius, Escherichia coli and Bacteroides fragilis) were selected, and their capacity to translocate in the in vitro M-cell model system and in vivo was confirmed. Results confirmed that differential translocation is evident at the level of the M cell in a pattern that is distinct from differential rates of internalization by monocytes for the same bacteria. Importantly, each bacterium was found to induce a different pattern of gene expression in M cells demonstrating for the first time an immunosensory discriminatory function of M cells to commensal bacteria.

Materials and methods

Animal housing conditions

Female BALB/c mice (Harlan, Bicester, Oxon, UK) aged 6–8 weeks were housed under specific pathogen-free conditions and received food and water ad libitum. Mice were killed by cervical dislocation. All animals were housed in conventional animal facilities cared for in compliance with protocols and procedures approved by the Animal Experimentation Ethics Committee of University College Cork.

Bacterial culture

Lactobacillus salivarius subsp. salivarius strain UCC118 was cultured at 37° under anaerobic conditions for 24 hr in de Man–Rogosa–Sharpe broth (Oxoid, Basingstoke, UK). Escherichia coli HB101 (German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany) was cultured in lysogeny broth at 37° under aerobic conditions for 24 hr with constant shaking. Bacteroides fragilis CIT01, kindly provided by Dr Jim O’Mahony, Cork Institute of Technology was cultured at 37° under anaerobic conditions for 24 hr in brain heart infusion broth (Oxoid) supplemented with 0·05%l-cysteine hydrochloride (Sigma, Dorset, UK). Bacterial viability was assessed using the Live/Dead BacLight viability and counting system (Invitrogen, Paisley, UK) in 0·85% sterile NaCl solution on an Accuri Flow cytometer (BD Biosciences, Erembodegem, Belgium). Plate counts were also performed for each strain with the respective agar plates and gave corresponding results to the Live/Dead stain protocol.

Generation of M-cell-like monolayer

The Caco-2 derivative C2BBe1 epithelial cell line (ATCC CRL-2102; American Type Culture Collection, Manassas, VA) was maintained in Dulbecco’s modified Eagle’s medium (DMEM; Gibco, Life Technologies, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS; Sigma), 100 μg/ml penicillin and 100 U/ml streptomycin (Gibco), 100 μm non-essential amino acids (Gibco) and 0·01 mg/ml transferrin (Calbiochem, San Diego, CA). C2BBe1 cells were seeded on a Millicell hanging cell culture insert (Millipore, Billerica, MA) with a 3·0-μm pore size at a density of 2 × 105 cells/insert and cultured for 21 days until the transepithelial electrical resistance was > 300 Ω·cm2 when cells were fully differentiated. Raji cells (a B-cell lymphocyte cell line; ATCC, CCL-86) maintained in DMEM supplemented with 10% FBS, 100 μg/ml penicillin and 100 U/ml streptomycin were added to the basal side of the cell culture insert at a concentration of 1 × 106 cells/ml for 72 hr to induce an M-cell-like phenotype.10,11 Control C2BBe1 cultures, without Raji co-culture, were also maintained in the porous culture inserts to be used as a differentiated enterocyte/epithelial control.

Translocation assay

Lactobacillus salivarius, E. coli or B. fragilis were labelled with 1 mmBacLight™ Red bacterial stain (Molecular Probes, Eugene, OR) and resuspended in 1× PBS (Gibco). The co-cultured epithelia (C2BBe1) and lymphocytes (Raji B cells), C2-M cells, were incubated at 4° for 1 hr before 1 × 108 of each labelled bacterium or control microspheres of 1 μm diameter (Molecular Probes) were introduced into the apical side of separate cell culture inserts. This 4° incubation was performed to ensure no paracellular transport of the bacteria from the apical to the basal compartment. The M-cell co-cultures, containing bacteria or beads, were then incubated at 37° for 30 min, 1, 2 or 3 hr. Following incubation, 300 μl basal medium, containing the transcytosed bacteria or beads, was collected into separate flow tubes (BD Biosciences, San Jose, CA) for translocation analysis by flow cytometry.

Flow cytometric analysis of translocation using fluorescent microspheres

Biotin-labelled yellow-green microspheres (Molecular Probes) were added to each 300-μl basal sample to give a concentration of 1 × 108 microspheres/sample. Samples were run through a BD FACSCalibur™ flow cytometer (BD Biosciences) until 10 000 bead events had been recorded.12 Data were analysed using CellQuest Pro software (BD Biosciences). The absolute count of bacteria per microlitre in each sample was calculated according to the following equation:

graphic file with name imm0136-0312-mu1.jpg

Real-time reverse transcription-PCR

Following co-culture and stimulation of cells with bacteria or beads the transwell filters containing the C2 or C2-M epithelial cells were removed and the basal side was rinsed briefly in a 12-well culture plate containing ice-cold PBS, removed and epithelia were then lysed by addition of RNA Lysis/Binding buffer (Ambion, Austin, TX) to the apical epithelia-containing side. Total RNA was then extracted using the mirVana™ miRNA Isolation Kit (Ambion). Nucleic acid concentration was quantified using a NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Waltham, MA). Reverse transcription was performed using an AffinityScript™ QPCR cDNA Synthesis Kit (Stratagene, Agilent Technologies, Santa Clara, CA). Individual PCR primer pairs and probes in addition to RealTime ready Human Pattern Recognition Receptor (PRR) Custom Panel, (Roche Applied Science, Indianapolis, IN) were designed using the Universal ProbeLibrary Assay Design Centre (http://www.roche-applied-science.com/sis/rtpcr/upl/ezhome.html). Primer sequences and probe combinations are provided in the Supplementary material, Tables S1 and S2. β-actin was used as a housekeeping gene. PCR (10 μl) contained 1 μl cDNA (of 100 μl), 5 μl of the 2× FastStart TaqMan® Probe Master (Roche), 900 nm of each primer and 250 nm probe mix. All reactions were in duplicate using 384-well plates on the LightCycler 480 System (Roche). Thermal cycling conditions were as recommended by the manufacturer (Roche). The Inline graphic method13 was used to calculate relative changes in gene expression determined from quantitative reverse transcription-PCR (qRT-PCR) experiments.

Affymetrix GeneChip® microarray

Microarray analysis on RNA extracted from C2-M cells incubated with L. salivarius, E.coli, B. fragilis or beads for 2 hr was performed by Cogenics (Beckman Coulter Genomics, Takeley, UK). Briefly, biotinylated cRNA was generated according to manufacturer’s instructions (Affymetrix, Santa Clara, CA), hybridized to Human Genome U133 Plus 2.0 Arrays (Affymetrix), washed and fluorescently labelled. The Affymetric GeneChips® were then scanned using the Affymetrix GeneChip Scanner 3000 and quantified using GeneChip Operating software (Affymetrix). For each ProbeSet, a ‘detection call’ was provided indicating whether the transcript was considered to be ‘present’, ‘absent’, or marginal. The GeneChip files were further analysed using GeneSpring 7.3.1 software (Silicon Genetics, Agilent Technologies, Santa Clara, CA). Hierarchical cluster analysis and visualization were performed using Genesis.14 All microarray data described in this study have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus database with the accession number GSE25330.

Cytokine and chemokine measurement

Measurement of secreted human interleukin-1β (IL-1β), IL-6, IL-8 and tumour necrosis factor-α (TNF-α) in culture supernatants was performed using an electro-chemiluminescence multiplex system Sector 2400 imager from Meso Scale Discovery (Gaithersburg, MD) where antibodies labelled with SULFO-TAG™ reagents emitted light upon electrochemical stimulation.

Oral gavage of fluorescently labelled bacteria to BALB/c mice

Lactobacillus salivarius, E. coli and B. fragilis were resuspended in PBS at a concentration of 1 × 109/ml, labelled with 1 mmBacLight™ Red bacterial stain (Molecular Probes) and finally resuspended in 100 μl PBS to give a concentration of 1 × 109 bacteria/100 μl. BALB/c mice were orally gavaged with 100 μl BacLight-labelled bacteria or control beads and were killed 2 hr after gavage. Intestines were dissected out and one 2-cm intestinal section containing a Peyer’s patch was frozen in liquid nitrogen for each experimental condition. Remaining Peyer’s patches were removed and placed in DMEM supplemented with 10% FBS, 100 μg/ml penicillin and 100 U/ml streptomycin and 2·5 μg/ml Fungizone® (Gibco) for isolation of M cells.

Isolation of murine M cells by GP2 selection

The follicle-associated epithelium was isolated from murine Peyer’s patches according to previously published methods.15 M cells were isolated by positive magnetic bead selection using the magnetic antibody cell-sorting (MACS) system (Miltenyi Biotech, Surrey, UK). Follicle-associated epithelial cells were resuspended in 0·01% EDTA for 15 min, filtered through a 30-μm cup Filcon cell filter (BD Biosciences) to remove cell aggregates and the filtrate was centrifuged and resuspended in degassed sample buffer [1 × PBS containing 0·5% BSA (Sigma) and 2 mm EDTA] at a concentration of 1 × 107 cells/100 μl. The cells were then incubated with 2 μg/ml anti-mouse glycoprotein 2 (GP2; MBL International, Woburn, MA) for 30 min at room temperature. Cells were washed twice with degassed sample buffer and resuspended in 90 μl of the sample buffer. The cell suspension was then incubated with 10 μl MACS anti-rat IgG MicroBeads (Miltenyi Biotech) at 4° for 15 min. The cell–bead suspension was washed by centrifugation and the cell–bead complex was resuspended in 500 μl degassed sample buffer. The sample was then applied to a MACS MS+ selection column (Miltenyi Biotech) in the presence of the MiniMACS high-energy permanent magnet (Miltenyi Biotech). The negative (non-GP2 binding) cells were allowed to flow through the column. The column was washed five times with degassed sample buffer and the fractions were pooled with the negative cells. The magnet was then removed and the positive (GP2 binding) cells were flushed out of the column. Both positive and negative samples were assessed for viability and enrichment using the Countess® Automated Cell Counter (Invitrogen). Cells were then resuspended in Lysis/Binding Buffer and the gene expression of Gp2 and Egr1 was assessed by qRT-PCR (see Supplementary material, Table S1 for primer sequences).

Histochemical staining of Peyer’s patch sections

Frozen intestinal sections were cut into 10-μm thick sections, which were fixed with 10% neutral buffered formalin (Sigma) and then permeabilized with 0·2% Triton-X-100 (Sigma). The plant lectin Ulex europaeus agglutinin 1 (UEA-1) was used to stain M cells. UEA-1-FITC (Vector Laboratories Ltd, Peterborough, UK) was added to cells at a concentration of 10 μg/ml. Cells were then counterstained with 0·165 μm DAPI (Molecular Probes). Cells were mounted with ProLong® Gold anti-fade reagent using No. 1·5 coverslips. Slides were viewed with an Olympus FV1000 confocal laser scanning microscope (Olympus, Hamburg, Germany).

Co-incubation of CFSE-labelled-biotinylated bacteria with monocytes

THP-1 monocytes (monocytic leukaemia cell line; ATCC, TIB 202) maintained in RPMI-1640 (Gibco) supplemented with 10% FBS, 100 μg/ml penicillin, 100 U/ml streptomycin and 0·05 mm 2-mercaptoethanol (Gibco) were seeded in six-well tissue culture dishes (Sarstedt, Nümbrecht, Germany) at a concentration of 1 × 106 cells/ml. Bacteria were cultured overnight, washed twice by centrifugation (3200 g for 10 min), and resuspended in PBS at a final concentration of 1 × 109 colony-forming units/ml. Bacteria (1 ml) were labelled with 10 μm carboxyfluorescein diacetate succinimidyl ester (CFSE, CellTrace™ Cell Proliferation Kit; Molecular Probes) for 15 min. Bacteria were then biotinylated using No-Weigh™N-hydroxysulphosuccinimide (Sulfo-NHS)-Biotin (Pierce, Thermo Scientific, Rockford, IL) according to the manufacturer’s instructions. The CFSE-labelled-biotinylated bacteria were added to the THP-1 cells at a multiplicity of infection of 10 : 1 and THP-1 cells and bacteria were co-incubated for 16 hr at 37° with 5% CO2. Supernatants were collected for later cytokine analysis and cell pellets from duplicate wells were resuspended in Lysis/Binding Buffer (mirVana™ miRNA Isolation Kit; Ambion) for gene expression analysis.

Flow cytometric analysis of bacterial uptake by THP-1 cells

The co-incubated THP-1 cells and bacteria were resuspended in streptavidin–allophycocyanin (Pierce) diluted 1 : 25 in 1% BSA (Sigma). Following streptavidin staining, cells were resuspended in PBS for flow cytometry analysis. Samples were run on a BD FACScalibur™ flow cytometer and data were analysed using CellQuest Pro software.

Confocal scanning laser microscopy

The co-incubated THP-1 cells and bacteria were washed twice in PBS, resuspended in 300 μl PBS and added to a Polysine slide (Thermo Scientific, Waltham, MA). The unbound cells were then aspirated after 30 min and the bound cells were fixed with 10% neutral buffered formalin. The cells were stained with streptavidin–allophycocyanin diluted 1 : 25 in 1% BSA for 30 min at 4°. Cells were permeabilized with 0·2% Triton X-100 (Sigma). Filamentous (F)-actin was stained with 0·165 μm rhodamine phalloidin (Molecular Probes) for 15 min. Cells were mounted with ProLong® Gold antifade reagent (Molecular Probes) using No. 1·5 coverslips (Marienfeld, Lauda-Königshofen, Germany). Slides were viewed with an Olympus FV1000 confocal laser scanning microscope (Olympus) consisting of an Olympus IX81 inverted microscope equipped with an oil-immersion Plan-Apo 60 ×/1·1 objective lens and a three-channel photomultiplier transmission detector using 1·5 × digital magnification. Five fields of view were collected from each slide to give a total of at least 100 cells per sample.

Statistical analyses

Statistical analysis was carried out using GraphPad Prism (version 4.03; GraphPad Software, San Diego, CA). Means with standard error (SEM) are presented in each graph. Differences between two groups were calculated using Student’s t-test. Differences between three or more groups were calculated by analysis of variance with Tukey’s post-hoc test. Differences were considered significant at P < 0·05. Microarray data were analysed using GeneSpring 7.3.1 software (Silicon Genetics) to determine significant changes with P < 0·05, and > 1·5-fold difference. To increase stringency, the cut-off was increased to twofold for some analyses where indicated. Cluster analysis and visualization were performed using Genesis14 and VENNY was used for visualization of differentially expressed data sets.16

Results

Different commensal bacteria translocate across an M-cell model with different efficiencies

To investigate possible responsiveness of M cells to commensal bacteria we used a well described in vitro model of M-cell function.10 Transepithelial electrical resistance was used to confirm the integrity of the C2BBe1 (C2) monolayer. The transepithelial electrical resistance values for the C2BBe1 (C2) control wells and co-cultured C2 plus Raji cells (C2-M) M cells were 475·2 ± 88·7 Ω·cm2 and 457·2 2 ± 71·4 Ω·cm2, respectively (data not shown). TNF receptor superfamily, member 9 (TNFRSF9) is induced by lymphocyte activation and is up-regulated in M cells17 and matrix metallopeptidase 15 (MMP15) has also been found to be up-regulated in M cells in vitro.18 Therefore, TNFRSF9 and MMP15 gene expression in C2 control cells and C2-M cells was examined by qRT-PCR to confirm that the C2 cells had been successfully converted into M-cell-like cells (Fig. 1a,b). There was a twofold (P < 0·05) and fourfold (P < 0·001) induction of TNFRSF9 and MMP15, respectively, when C2 cells were co-incubated with Raji cells, confirming the induction of an M-cell model (Fig. 1a,b). To characterize the M cells further in terms of their potential to recognize microbe-associated molecular patterns we screened by qRT-PCR for the expression of 50 PRRs comparing C2-M with C2 cells. We noticed that C2-M cells had significantly higher levels of mannose receptor c type 1 (MRC1; 100-fold, P < 0·001), nucleotide-binding oligomerization domain containing 1 (NOD1; twofold, P < 0·001), Toll-like receptor 3 (TLR3), TLR5 and TLR6 (twofold, 80-fold and threefold, P < 0·001, P < 0·001 and P < 0·05, respectively). C2-M cells have reduced expression of nucleotide-binding domain leucine-rich repeat-containing proteins (NLR) family, CARD-domain-containing 5 (NLRC-5; 56-fold, P < 0·001) and NLR family, pyrin-domain-containing 3 (NLRP-3; 55-fold, P < 0·001), see Supplementary material, Figs S1 and S2.

Figure 1.

Figure 1

Open in a new tab

Translocation of commensal bacteria across an in vitro M-cell model and in vivo murine Peyer’s patch M cells. Induction of M-cell phenotype was confirmed by quantitative reverse transcription-PCR for TNFRSF9 (a) and MMP-15 (b) Data are presented as means + SEM, n = 3. Translocation of bacteria was assessed (c) by adding Lactobacillus salivarius, Escherichia coli or Bacteroides fragilis to C2-M cells for 30 min, 1, 2 or 3 hr and the number of bacteria in the basal supernatant was measured by flow cytometry: L. salivarius (open square), E. coli (closed triangle) and B. fragilis (open circle). Data are presented as means + SEM, n = 6, *P < 0·05, L. salivarius compared with B. fragilis; **P < 0·01 L. salivarius versus B. fragilis and E. coli. C2-M cells had a higher basal expression of CCL20 (d) than C2 cells and addition of E. coli and B. fragilis to C2-M cells increased CCL20 expression compared with unstimulated C2-M cells. Data are presented as means + SEM, n = ### P < 0·001, C2-M compared with C2. ***P < 0·001, compared with C2-M. C2-M cells had a significantly higher basal expression of CLDN4 (e) than C2 cells but addition of B. fragilis to C2-M cells decreased CLDN4 expression compared with unstimulated C2-M cells. Data are presented as means + SEM, n = ### P < 0·001, C2-M compared with C2, **P < 0·01, compared with C2-M. Peyer’s patch sections taken 2 hr post-gavage with BacLight Red-labelled L. salivarius (f), E. coli (g) and B. fragilis (h) were stained with UEA-1-FITC (green) and nuclei (blue) were counter-stained with DAPI. Images were taken at 20 × (f) or 40 × (g,h), Scale bar represents 10 μm. Schematic box in (f), V represents villi, FAE, represents follicle associated epithelium, and SED indicates sub-epithelial dome.

The translocation rate of three strains of commensal bacteria across the M cell model was measured by flow cytometry. Bacteroides fragilis and E. coli translocated with the highest efficiency, with 1·8 × 105B. fragilis and 1·5 × 105E. coli detected per ml after 30 min (Fig. 1c). Lactobacillus salivarius translocated with the lowest efficiency at 3·7 × 104/ml at 30 min, which was statistically lower than B. fragilis (P < 0·05; Fig. 1c). At 1 hr the translocation of L. salivarius was statistically lower than both B. fragilis and E. coli (P < 0·01; Fig. 1c). No bacteria were detected in the basal supernatant following co-incubation of the bacteria and cells at 4°, and this confirms that translocation of the bacteria was an active process and occurred via the transcellular and not the paracellular route (data not shown). None of the bacterial treatments altered the transepithelial electrical resistance value of the monolayer compared with the control cells at any time-point and the viability of bacteria in the apical medium remained unchanged among the bacteria for the duration of the experiment. All strains were 89 ± 5% viable following transcytosis as determined by Live–Dead staining.

To further confirm functional responsiveness of the M-cell model we first evaluated expression of the CC chemokine CCL20 (MIP-3α) and tight junction protein Claudin-4 (CLDN4) genes in C2-M cells. CCL20 is considered to be a follicle-associated epithelium-specific gene17 and a dendritic cell chemoattractant.19 Claudin-4 has previously been shown to be induced in C2BBe1 cells co-cultured with Raji cells and also in M cells in vivo. Co-incubation of C2 cells with Raji cells to generate the C2-M phenotype increased expression of CCL20 fivefold, and addition of E. coli and B. fragilis to C2-M cells significantly increased CCL20 expression further (P < 0·01; Fig. 1d). Lactobacillus salivarius did not increase CCL20 expression in C2-M cells (Fig. 1d). We confirmed previously published findings regarding the M-cell marker gene CLDN4, as C2-M cells had a fivefold increase in the expression of CLDN4 compared with C2 cells. Addition of bacteria to C2-M cells decreased CLDN4 expression, but this decrease was only significant (P < 0·01) in the case of B. fragilis (Fig. 1e). The three commensals had a different effect on control C2 cells compared with C2-M cells; L. salivarius, E. coli and B. fragilis increased CCL20 (P < 0·01, P < 0·001 and P < 0·001, respectively), whereas all strains increased CLDN4 expression (P < 0·001), see Supplementary material, Fig. S3a,b.

To confirm that each of the commensal strains was capable of being translocated by M cells in vivo, mice were orally challenged with each bacterium. All three strains were translocated within 2 hr across M cells into the underlying sub-epithelial dome, with no difference in translocation efficiency being observed at this time-point (Fig. 1f–h). Co-localization of the labelled bacteria and M cells can be seen in the Supplementary material, Fig. S4a,b.

Differential gene expression by M cells in response to different commensals

To further evaluate if the differing rates of transcytosis observed were associated with differential mRNA expression by the M cells, genome-wide gene expression analysis was performed on C2-M cells that had been co-incubated with L. salivarius, E. coli, B. fragilis or control polystyrene beads [comparable size (1 μm) to the bacteria]. Statistical analysis was performed to identify differentially expressed genes, with the selection criteria being a > 1·5-fold or twofold change with significance of P ≤ 0·05. The numbers of common and different gene expression changes among L. salivarius, E. coli, B. fragilis and control beads are illustrated in a Venn diagram (Fig. 2), gene lists representing each intersection are provided in the Supplementary material, Table S3. Following differential gene identification, gene cluster analysis was performed to reveal genes that were common and different to each of the bacteria and the beads (Fig. 3). Sixty-five genes were increased or decreased by the bacteria and the beads using a twofold minimum cut-off and P < 0·05. The data cluster into seven distinct clusters depending on shared gene induction patterns – for example Cluster 5 identifies genes that are increased in the presence of L. salivarius, E. coli and B. fragilis but not beads. These genes are EGR1 (early growth response 1), DUSP1 (dual specificity phosphatase 1), FOS (FBJ murine osteosarcoma viral oncogene homologue), JUN (jun oncogene) and ZFP36 (zinc finger protein 36, C3H type, homologue), which are mainly involved in transcription regulation and dephosphorylation. Cluster 3 shows genes that are increased in the presence of E. coli and B. fragilis but not by L. salivarius or beads. These genes are predominantly pro-inflammatory or stress response genes and include OLR1 [oxidized low-density lipoprotein (lectin-like) receptor 1], CXCL1 [chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity alpha)], IL8 (interleukin 8), NFKBIZ (nuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor zeta), CXCL2 [chemokine (C-X-C motif) ligand 2], NFKBIA (nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha) and TNFAIP3 (tumour necrosis factor alpha-induced protein 3). Visualization of the gene expression network induced by the commensal bacteria was also performed; see Supplementary material, Fig. S5, showing interactions of transcription factors and various chemokines induced by the bacteria.

Figure 2.

Figure 2

Open in a new tab

Venn diagram illustrating the common and different gene expression changes induced by Lactobacillus salivarius, Escherichia coli, Bacteroides fragilis and beads in C2-M cells. A 1·5-fold change was used as a cut-off for selection criteria. Corresponding alphabetic listing of the genes common to each set is provided in Supplementary material, Table S2.

Figure 3.

Figure 3

Open in a new tab

Cluster analysis of C2-M microarray data. Heat map of hierarchical cluster analysis showing 65 genes changed 2·0-fold in C2-M cells by the presence of Lactobacillus salivarius, Escherichia coli, Bacteroides fragilis and beads. Green indicates a decrease in gene expression, while red indicates an increase. Data are categorized into seven different clusters showing expression profiles depending on treatment.

The microarray data results were confirmed for selected genes reflecting different clusters by qRT-PCR; IL8 and EGR1 are induced by E. coli (P < 0·01) and B. fragilis (P < 0·001, P < 0·01, respectively) but not by L. salivarius or beads (Fig. 4a,b). The microarray data were also confirmed for ANKRD37 (ankrin repeat domain 37), which was induced by all bacteria, and NR4A1 (nuclear receptor subfamily 4, group A, member 1) which is reduced during transcytosis of bacteria and beads (Fig. 4c,d). The qRT-PCR was also performed on control C2 cells cultured with the three bacteria to determine if the genes induced were M-cell-specific or induced in all epithelia, irrespective of phenotype, by the bacteria assayed. IL8 was undetectable and EGR1 showed no induction of expression, (see Supplementary material, Fig. S6a). The lack of induction of TNFAIP3 by L. salivarius, as observed in the C2-M microarray data, was also observed in C2 cells (Fig. S6b). NR4A1 was induced by all bacteria (P < 0·01) and ANKRD37 showed significant reduction by the three commensals (P < 0·01), see Fig. S6c,d.

Figure 4.

Figure 4

Open in a new tab

Confirmation of differential microarray gene expression in C2-M cells. C2-M cells were incubated with Lactobacillus salivarius, Escherichia coli, Bacteroides fragilis or beads for 2 hr and IL8 (a), EGR1 (b), ANKRD37 (c) and NR4A1 (d) gene expression was measured quantitative reverse transcription-PCR. Data are presented as means + SEM, n = 3. ***P < 0·001, **P < 0·01, compared with C2-M.

Commensal bacteria differentially activate murine M cells in vivo

Following these observations we evaluated if these changes in gene expression also occurred in M cells in vivo. Confirmation of translocation across M cells following oral challenge had already been observed for all three strains (Fig. 1f–h). To determine the M-cell expression profile, we isolated a pure M-cell population using anti-GP2 antibody to positively select from a mixed follicle-associated epithelium preparation. Cells isolated by this method had higher gene expression of GP2 compared with the surrounding follicle-associated epithelium (Fig. 5a), hence validating GP2 as a method of selection. Given that EGR1 was differentially activated by the bacteria and the polystyrene beads in vitro (Fig. 5b), the expression of Egr1 in GP2-positive cells was examined. The expression of Egr1 was sixfold higher (P < 0·001) in M cells isolated from mice that had been orally challenged with B. fragilis compared with those that had been gavaged with PBS, but no other treatment resulted in a change in Egr1 expression (Fig. 5b).

Figure 5.

Figure 5

Open in a new tab

Commensal bacteria differentially activate Peyer’s patch M cells in vivo. Cells isolated by GP2-positive selection have higher basal GP2 (a) gene expression. Data are presented as means + SEM, n = 3. ***P < 0·001, compared with follicle-associated epithelium GP2-negative. Oral challenge with Bacteroides fragilis increases Egr1 (b) expression in GP2-positive cells. Data are presented as means + SEM, n = 3. ***P < 0·001, compared with GP2 positive M cells.

Monocyte uptake of commensal bacteria is different from that of M-cell uptake but immunosensory response is similar

To confirm that L. salivarius was recognized by immune cells, fluorescently labelled L. salivarius, E. coli and B. fragilis were co-incubated with THP-1 monocytes for 16 hr and the uptake of each strain was assessed using flow cytometry and confocal laser scanning microscopy. Flow cytometry showed that all three strains were internalized by THP-1 cells but in contrast to the M-cell translocation results, L. salivarius was internalized by THP-1 cells at a higher rate (54%) than E. coli (31%) or B. fragilis (22%; Fig. 6a). Confocal laser scanning microscopic analysis confirmed this observation, (Fig. 6b). In addition, THP-1 cells that were co-incubated with L. salivarius had significantly less production of the pro-inflammatory cytokines IL-1β, IL-6 and TNF-α (P < 0·01 and P < 0·001) than THP-1 cells incubated with B. fragilis or E. coli (Fig. 6c–e). In contrast, THP-1 cells co-incubated with L. salivarius had increased production of the chemokine IL-8 compared with THP-1 cells that were co-incubated with B. fragilis or E. coli (P < 0·05; Fig. 6f).

Figure 6.

Figure 6

Open in a new tab

THP-1 monocytes internalize commensal bacteria with different efficiencies and have a differential cytokine profile depending on the strain. Internalization (a) of Lactobacillus salivarius, Escherichia coli and Bacteroides fragilis by THP-1 cells after 16 hr co-incubation was assessed by flow cytometry. Flow cytometric results were confirmed by confocal laser scanning microscopy for L. salivarius (b). Inset shows zoom of indicated region. Scale bar represents 10 μm. The production of interleukin-1 β (IL-1β) (c), IL-6 (d), tumour necrosis factor-α (TNF-α) (e) and IL-8 (f) by THP-1 cells was measured in unstimulated THP-1 cells and in THP-1 cells co-incubated with each strain of bacteria. Values are shown as mean ± SEM, n = 3. *P < 0·05, **P < 0·01, ***P < 0·001 Bacterial strains compared with unstimulated control.

Discussion

The aim of this study was twofold: (i) to assess the translocation of different commensal bacteria across M cells and (ii) to assess the capacity of M cells for immunosensory discriminatory responses to these same bacteria. Although many studies have examined the rate of translocation of pathogens, fewer studies have examined translocation of non-pathogenic commensal bacteria, which are constantly sampled by M cells within the gut and may even reside in Peyer’s patches under normal physiological conditions.10,20–22 As the normal gut flora belong predominantly to two phyla; the Firmicutes and the Bacteroidetes, we chose L. salivarius and B. fragilis to represent each of these phyla and a non-pathogenic E. coli as a second common commensal bacterium.23

This study demonstrates that these three different commensal bacteria translocate in vitro across an M-cell monolayer with varying efficiencies. An unexpected finding was that B. fragilis translocated with the greatest efficiency, as previous in vivo studies have shown that it is the least efficient commensal at translocating across M cells to the mesenteric lymph nodes.24 This discrepancy may be accounted for in part by species differences in M-cell surface properties and function between human cells in culture and gnotobiotic mice as used in the original study. Some M-cell receptor/microbe ligand interactions have been characterized, including β1 integrin/Yersinia spp., α(2,3) sialic acid/reovirus and GP2/FimH-positive bacteria, but it is likely that many more remain to be discovered.25–28 For example, Chassaing et al.29 recently observed that the presence of long polar fimbriae enhances adherent-invasive E. coli translocation in M-cell monolayers, although the respective receptor in this instance was not identified.

Microarray analysis of the C2-M cells revealed that each commensal bacterium induced different gene expression patterns in M cells, with E. coli and B. fragilis inducing the most similar gene expression changes. Lactobacillus salivarius was associated with the least number of gene expression changes in M cells, which perhaps reflects both its lower translocation rate and cell surface properties. Polystyrene beads were used as a control with common genes induced by the beads and the bacteria, suggesting that these genes may represent a gene signature related to M-cell translocation. There were, however, genes that were specifically induced by the bacteria but not by the beads. These genes included the transcription factors that mediate the immediate-early response EGR1, FOS and JUN, the negative regulator ZFP36, and the phosphatase DUSP1. These genes have previously been linked by cluster analysis in studies examining the response of human epithelial lung cells to avian influenza, endothelial cells stimulated with IL-1 and in tumour microarray analyses.30–32 The selective activation of these genes by the bacteria but not the beads indicates that the bacteria are activating and being sensed by the M cells, whereas the beads are merely being translocated non-specifically. Escherichia coli and B. fragilis also activated more pro-inflammatory genes than L. salivarius, which again may be related to the lower translocation efficiency of L. salivarius. These inflammatory genes included the chemokines CXCL1, CXCL2 and IL8 which are potent chemoattractants for neutrophils and other immune cell types.

Neutrophil recruitment is critical for clearance of bacteria once they have translocated the epithelium.33–35CXCL2 has also been shown to be up-regulated in vivo in Peyer’s patches and mesenteric lymph nodes coincident with the accumulation of monocytes and neutrophils in these tissues.36 It is interesting to note that the increased translocation efficiency of E. coli and B. fragilis compared with L. salivarius, was associated with a more potent induction of pro-inflammatory genes. NFKBIZ, NFKBIA and TNFAIP3 inhibit nuclear factor-κB signalling via a negative feedback loop.37–39NFKBIZ is induced by lipopolysaccharide, which could explain why it is induced by E. coli and B. fragilis but not L. salivarius.40 The microarray data were confirmed by qRT-PCR for selected genes, including IL8 and EGR1, and the same changes for each of the bacteria and the beads were observed, which validates our microarray findings. The gene ANKRD37, an HIF1α-inducible gene, was also confirmed, illustrating activation by all three bacterial species,41 whereas the gene, NR4A1, which is involved with fibronectin adhesion,42 was reduced in expression in C2-M cells treated with bacteria and the beads.

It is also interesting to note that we observed differential expression of PRRs in C2-M cells compared with control differentiated C2 cells. MRC1 was highly expressed in C2-M cells compared with C2 cells and has previously been observed by Hase et al.43 to be increased in the follicle-associated epithelium overlying the murine Peyer’s patch. MRC1 is an endocytic and a phagocytic receptor which binds a variety of microbial glycoproteins and allergens; it is involved with dendritic cell function and has been postulated to be involved with M-cell macromolecule transcytosis.43,44 In addition to MRC1, we also found that the expression of two intracellular PRRs, the NLRs, NLRP3 and NLRC5 were down-regulated in C2-M relative to C2 cells. The proteins encoded by these two genes can interact and form a complex contributing in a co-operative way to the formation of the inflammasome in host cells thereby triggering a potent pro-inflammatory response through release of IL-1β and IL-18.45 Consistent with the difference in expression of PRRs between C2-M and C2 cells, we also observed that the three commensal bacteria induced a different epithelial response in the C2 cells compared with the C2-M cells, further illustrating the specialized role of M cells in sampling and recognition compared with enterocytes. In future studies, it will be interesting to use this M-cell model in combination with gene disruptive approaches such as RNAi to dissect out the PRRs required for the M-cell response to different commensal bacteria.

The ability of M cells to discriminate between different strains of bacteria and inert latex beads was not limited to the in vitro model. M cells isolated from mice that had been orally challenged with B. fragilis had a higher expression of Egr1, which mirrors the in vitro result. Lactobacillus salivarius and E. coli did not activate Egr1 in vivo, however, which is in contrast to the in vitro result. This discrepancy between in vitro and in vivo may be the result of species differences in M-cell surface properties and function between human M cells in culture and mouse M cells and their specific recognition of individual bacterial strains, the nature of the bacterial strains or their behaviour in vitro versus in vivo.

Once bacteria and particles translocate through the M cells in vivo, they encounter underlying immune cells including dendritic cells, lymphocytes and monocytes. For this reason, the internalization of bacteria by human monocytes was examined. THP-1 cells had a different pattern of internalization to M cells and, of note, L. salivarius was internalized by the monocytes with the highest efficiency and induced the lowest production of pro-inflammatory cytokines. This confirms that L. salivarius is recognized by immune cells and is not evading the immune system, despite its lower translocation rate across M cells. The fact that both M cells and THP-1 cells produce minimal pro-inflammatory mediators in response to L. salivarius, in contrast to their response to E. coli and B. fragilis, is consistent with an immunosensory function for the follicle-associated epithelium.

In conclusion, while M cells have previously been thought of as ‘unintelligent translocators’ of gut bacteria, we have shown that they are capable of discriminating between different commensal bacteria. This suggests that there is immunosensory discrimination by epithelial cells at the first step of bacterial sampling within the gut.

Acknowledgments

The Alimentary Pharmabiotic Centre is a research centre funded by Science Foundation Ireland (SFI), through the Irish Government’s National Development Plan. We would like to thank Trevor Darby for provision of control C2 non-polarized RNA samples. The authors and their work are supported by SFI grant numbers: 02/CE/B124 and 07/CE/B1368.

Disclosures

The authors have no conflicting financial interests.

Supporting information

Additional Supporting Information may be found in the online version of this article:

Figure S1. Evaluation of PRR expression in non polarised C2, polarised C2 and polarised C2-M epithelia-I, CD302 (a), CD302 (b), NLRP3 (c) NLRP11 (D), NOD1(e), NLRC5 (f), CLEC4A (g) and MYD88 (h) expression was measured by qRT-PCR.

Figure S2. Evaluation of PRR expression in non polarised C2, polarised C2 and polarised C2-M epithelia-II, RIPK2 (a), TLR1 (b), TLR2 (c) TLR3 (d), TLR5 (e), TLR6 (f), TLR7 (g) and TLR8 (h) expression was measured by qRT-PCR.

Figure S3. Commensal bacteria induce CCL20 and CLDN4 gene expression in polarised C2 cells.

Figure S4. Co-localisation and translocation ofcommensal bacteria in murine Peyer’s patch M cells.

Figure S5. Pathway analysis of gene expression profiles of C2-M cells incubated with commensal bacteria.

Figure S6. The effect of commensal bacteria on gene expression of microarray identified gene candidates in polarised C2 cells.

Table S1. List of PCR primers and probes used in this study.

Table S2. List of PCR primers used in the PRR gene expression screen used in this study.

Table S3. List of genes present in each data set corresponding to Fig. 2.

imm0136-0312-SD1.pptx (4MB, pptx)
imm0136-0312-SD2.docx (15.3KB, docx)
imm0136-0312-SD3.docx (124.3KB, docx)

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

References

  • 1.Whitman WB, Coleman DC, Wiebe WJ. Prokaryotes: the unseen majority. Proc Natl Acad Sci U S A. 1998;95:6578–83. doi: 10.1073/pnas.95.12.6578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Garrett WS, Gordon JI, Glimcher LH. Homeostasis and inflammation in the intestine. Cell. 2010;140:859–70. doi: 10.1016/j.cell.2010.01.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Pickard JM, Chervonsky AV. Sampling of the intestinal microbiota by epithelial M cells. Curr Gastroenterol Rep. 2010;12:331–9. doi: 10.1007/s11894-010-0128-x. [DOI] [PubMed] [Google Scholar]
  • 4.Bockman DE, Cooper MD. Pinocytosis by epithelium associated with lymphoid follicles in the bursa of Fabricius, appendix, and Peyer’s patches. An electron microscopic study. Am J Anat. 1973;136:455–77. doi: 10.1002/aja.1001360406. [DOI] [PubMed] [Google Scholar]
  • 5.Owen RL, Jones AL. Epithelial cell specialization within human Peyer’s patches: an ultrastructural study of intestinal lymphoid follicles. Gastroenterology. 1974;66:189–203. [PubMed] [Google Scholar]
  • 6.Neutra MR, Phillips TL, Mayer EL, Fishkind DJ. Transport of membrane-bound macromolecules by M cells in follicle-associated epithelium of rabbit Peyer’s patch. Cell Tissue Res. 1987;247:537–46. doi: 10.1007/BF00215747. [DOI] [PubMed] [Google Scholar]
  • 7.Miller H, Zhang J, Kuolee R, Patel GB, Chen W. Intestinal M cells: the fallible sentinels? World J Gastroenterol. 2007;13:1477–86. doi: 10.3748/wjg.v13.i10.1477. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Macpherson AJ, Uhr T. Induction of protective IgA by intestinal dendritic cells carrying commensal bacteria. Science. 2004;303:1662–5. doi: 10.1126/science.1091334. [DOI] [PubMed] [Google Scholar]
  • 9.Berg RD, Garlington AW. Translocation of certain indigenous bacteria from the gastrointestinal tract to the mesenteric lymph nodes and other organs in a gnotobiotic mouse model. Infect Immun. 1979;23:403–11. doi: 10.1128/iai.23.2.403-411.1979. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Kerneis S, Bogdanova A, Kraehenbuhl J-P, Pringault E. Conversion by Peyer’s patch lymphocytes of human enterocytes into M cells that transport bacteria. Science. 1997;277:949–52. doi: 10.1126/science.277.5328.949. [DOI] [PubMed] [Google Scholar]
  • 11.Gullberg E, Leonard M, Karlsson J, Hopkins AM, Brayden D, Baird AW, Artursson P. Expression of specific markers and particle transport in a new human intestinal M-Cell model. Biochem Biophys Res Commun. 2000;279:808–13. doi: 10.1006/bbrc.2000.4038. [DOI] [PubMed] [Google Scholar]
  • 12.Chang WL, van der Heyde HC, Klein BS. Flow cytometric quantitation of yeast a novel technique for use in animal model work and in vitro immunologic assays. J Immunol Methods. 1998;211:51–63. doi: 10.1016/s0022-1759(97)00191-9. [DOI] [PubMed] [Google Scholar]
  • 13.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods. 2001;25:402–8. doi: 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
  • 14.Sturn A, Quackenbush J, Trajanoski Z. Genesis: cluster analysis of microarray data. Bioinformatics. 2002;18:207–8. doi: 10.1093/bioinformatics/18.1.207. [DOI] [PubMed] [Google Scholar]
  • 15.Cashman SB, Morgan JG. Transcriptional analysis of Toll-like receptors expression in M cells. Mol Immunol. 2009;47:365–72. doi: 10.1016/j.molimm.2009.09.007. [DOI] [PubMed] [Google Scholar]
  • 16.Oliveros JC. VENNY. An interactive tool for comparing lists with venn diagrams. 2007. [Google Scholar]
  • 17.Wang J, Lopez-Fraga M, Rynko A, Lo DD. TNFR and LTβR agonists induce follicle-associated epithelium and M cell specific genes in rat and human intestinal epithelial cells. Cytokine. 2009;47:69–76. doi: 10.1016/j.cyto.2009.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Lo D, Tynan W, Dickerson J, et al. Cell culture modeling of specialized tissue: identification of genes expressed specifically by follicle-associated epithelium of Peyer’s patch by expression profiling of Caco-2/Raji co-cultures. Int Immunol. 2004;16:91–9. doi: 10.1093/intimm/dxh011. [DOI] [PubMed] [Google Scholar]
  • 19.Izadpanah A, Dwinell MB, Eckmann L, Varki NM, Kagnoff MF. Regulated MIP-3α/CCL20 production by human intestinal epithelium: mechanism for modulating mucosal immunity. Am J Physiol Gastrointest Liver Physiol. 2001;280:G710–9. doi: 10.1152/ajpgi.2001.280.4.G710. [DOI] [PubMed] [Google Scholar]
  • 20.Fujimura Y. Functional morphology of microfold cells (M cells) in Peyer’s patches – phagocytosis and transport of BCG by M cells into rabbit Peyer’s patches. Gastroenterol Jpn. 1986;21:325–35. [PubMed] [Google Scholar]
  • 21.Jang MH, Kweon M-N, Iwatani K, et al. Intestinal villous M cells: an antigen entry site in the mucosal epithelium. Proc Natl Acad Sci U S A. 2004;101:6110–5. doi: 10.1073/pnas.0400969101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Obata T, Goto Y, Kunisawa J, et al. Indigenous opportunistic bacteria inhabit mammalian gut-associated lymphoid tissues and share a mucosal antibody-mediated symbiosis. Proc Natl Acad Sci U S A. 2010;107:7419–24. doi: 10.1073/pnas.1001061107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hugenholtz P, Goebel BM, Pace NR. Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity. J Bacteriol. 1998;180:4765–74. doi: 10.1128/jb.180.18.4765-4774.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Steffen EK, Berg RD, Deitch EA. Comparison of translocation rates of various indigenous bacteria from the gastrointestinal tract to the mesenteric lymph node. J Infect Dis. 1988;157:1032–8. doi: 10.1093/infdis/157.5.1032. [DOI] [PubMed] [Google Scholar]
  • 25.Autenrieth IB, Firsching R. Penetration of M cells and destruction of Peyer’s patches by Yersinia enterocolitica: an ultrastructural and histological study. J Med Microbiol. 1996;44:285–94. doi: 10.1099/00222615-44-4-285. [DOI] [PubMed] [Google Scholar]
  • 26.Hase K, Kawano K, Nochi T, et al. Uptake through glycoprotein 2 of FimH+ bacteria by M cells initiates mucosal immune response. Nature. 2009;462:226–30. doi: 10.1038/nature08529. [DOI] [PubMed] [Google Scholar]
  • 27.Wolf J, Rubin D, Finberg R, Kauffman R, Sharpe A, Trier J, Fields B. Intestinal M cells: a pathway for entry of reovirus into the host. Science. 1981;212:471–2. doi: 10.1126/science.6259737. [DOI] [PubMed] [Google Scholar]
  • 28.Helander A, Silvey KJ, Mantis NJ, Hutchings AB, Chandran K, Lucas WT, Nibert ML, Neutra MR. The viral σ1 protein and glycoconjugates containing α2-3-linked sialic acid are involved in type 1 reovirus adherence to M cell apical surfaces. J Virol. 2003;77:7964–77. doi: 10.1128/JVI.77.14.7964-7977.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Chassaing B, Rolhion N, Vallée AD, et al. Crohn disease-associated adherent-invasive E. coli bacteria target mouse and human Peyer’s patches via long polar fimbriae. J Clin Investig. 2011;121:966–75. doi: 10.1172/JCI44632. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Tatebe K, Zeytun A, Ribeiro R, Hoffmann R, Harrod K, Forst C. Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections. BMC Bioinformatics. 2010;11:170. doi: 10.1186/1471-2105-11-170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Mayer H, Bilban M, Kurtev V, Gruber F, Wagner O, Binder BR, de Martin R. Deciphering regulatory patterns of inflammatory gene expression from interleukin-1-stimulated human endothelial cells. Arterioscler Thromb Vasc Biol. 2004;24:1192–8. doi: 10.1161/01.ATV.0000131263.06296.77. [DOI] [PubMed] [Google Scholar]
  • 32.Becker JAJ, Mirjolet J-F, Bernard J, Burgeon E, Simons M-J, Vassart G, Parmentier M, Libert F. Activation of GPR54 promotes cell cycle arrest and apoptosis of human tumor cells through a specific transcriptional program not shared by other Gq-coupled receptors. Biochem Biophys Res Commun. 2005;326:677–86. doi: 10.1016/j.bbrc.2004.11.094. [DOI] [PubMed] [Google Scholar]
  • 33.Geiser T, Dewald B, Ehrengruber MU, Clark-Lewis I, Baggiolini M. The interleukin-8-related chemotactic cytokines GROα, GROβ, and GROγ activate human neutrophil and basophil leukocytes. J Biol Chem. 1993;268:15419–24. [PubMed] [Google Scholar]
  • 34.Wolpe SD, Sherry B, Juers D, Davatelis G, Yurt RW, Cerami A. Identification and characterization of macrophage inflammatory protein 2. Proc NatL Acad Sci U S A. 1989;86:612–6. doi: 10.1073/pnas.86.2.612. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Yoshimura T, Matsushima K, Tanaka S, Robinson EA, Appella E, Oppenheim JJ, Leonard EJ. Purification of a human monocyte-derived neutrophil chemotactic factor that has peptide sequence similarity to other host defense cytokines. Proc Natl Acad Sci U S A. 1987;84:9233–7. doi: 10.1073/pnas.84.24.9233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Rydström A, Wick MJ. Monocyte and neutrophil recruitment during oral Salmonella infection is driven by MyD88-derived chemokines. Eur J Immunol. 2009;39:3019–30. doi: 10.1002/eji.200939483. [DOI] [PubMed] [Google Scholar]
  • 37.Yamazaki S, Muta T, Takeshige K. A novel IκB protein, IκB-ζ, induced by proinflammatory stimuli, negatively regulates nuclear factor-κB in the nuclei. J Biol Chem. 2001;276:27657–62. doi: 10.1074/jbc.M103426200. [DOI] [PubMed] [Google Scholar]
  • 38.Haskill S, Beg AA, Tompkins SM, et al. Characterization of an immediate-early gene induced in adherent monocytes that encodes IκB-like activity. Cell. 1991;65:1281–9. doi: 10.1016/0092-8674(91)90022-q. [DOI] [PubMed] [Google Scholar]
  • 39.Wertz IE, O’Rourke KM, Zhou H, et al. De-ubiquitination and ubiquitin ligase domains of A20 downregulate NF-κB signalling. Nature. 2004;430:694–9. doi: 10.1038/nature02794. [DOI] [PubMed] [Google Scholar]
  • 40.Kitamura H, Kanehira K, Okita K, Morimatsu M, Saito M. MAIL, a novel nuclear IκB protein that potentiates LPS-induced IL-6 production. FEBS Lett. 2000;485:53–6. doi: 10.1016/s0014-5793(00)02185-2. [DOI] [PubMed] [Google Scholar]
  • 41.Benita Y, Kikuchi H, Smith AD, Zhang MQ, Chung DC, Xavier RJ. An integrative genomics approach identifies hypoxia inducible factor-1 (HIF-1)-target genes that form the core response to hypoxia. Nucleic Acids Res. 2009;37:4587–602. doi: 10.1093/nar/gkp425. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Alexopoulou AN, Leao M, Caballero OL, et al. Dissecting the transcriptional networks underlying breast cancer: NR4A1 reduces the migration of normal and breast cancer cell lines. Breast Cancer Res. 2010;12:R51. doi: 10.1186/bcr2610. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Hase K, Ohshima S, Kawano K, Hashimoto N, Matsumoto K, Saito H, Ohno H. Distinct gene expression profiles characterize cellular phenotypes of follicle-associated epithelium and M cells. DNA Res. 2005;12:127–37. doi: 10.1093/dnares/12.2.127. [DOI] [PubMed] [Google Scholar]
  • 44.Royer PJ, Emara M, Yang C, et al. The mannose receptor mediates the uptake of diverse native allergens by dendritic cells and determines allergen-induced T cell polarization through modulation of IDO activity. J Immunol. 2010;185:1522–31. doi: 10.4049/jimmunol.1000774. [DOI] [PubMed] [Google Scholar]
  • 45.Davis BK, Roberts RA, Huang MT, et al. Cutting edge: NLRC5-dependent activation of the inflammasome. J Immunol. 2011;186:1333–7. doi: 10.4049/jimmunol.1003111. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

imm0136-0312-SD1.pptx (4MB, pptx)
imm0136-0312-SD2.docx (15.3KB, docx)
imm0136-0312-SD3.docx (124.3KB, docx)

Articles from Immunology are provided here courtesy of British Society for Immunology

RESOURCES