Conceived and designed the experiments: MJW JML MD MAP IC PL. Performed the experiments: MJW JML MD. Analyzed the data: MJW JML. Contributed reagents/materials/analysis tools: MAP IC PL. Wrote the paper: MJW PL.
The authors have declared that no competing interests exist.
There is increasing evidence that dysregulation of CD4+ T cell populations leads to intestinal inflammation, but the regional distribution of these populations throughout the intestinal tract in healthy individuals remains unclear. Here, we show that TH17, TH22 and TReg cells are enriched in the healthy human cecum compared to the terminal ileum and sigmoid colon, whereas TH1 and TH2 cells do not significantly vary by location. Transcriptional profiling analysis of paired pinch biopsies from different regions of the intestine identified significant differences in the metabolic state of the terminal ileum, cecum, and sigmoid colon. An increased proportion of TH17 cells was positively associated with expression of resistin (RETN) and negatively associated with expression of trefoil factor 1 (TFF1). These results suggest that CD4+ T helper cells that are important in maintaining mucosal barrier function may be enriched in the cecum as a result of metabolic differences of the surrounding microenvironment.
The human intestinal epithelium represents a critical interface between our entire internal milieu and the outside world
In order to better understand how dysregulation among populations of CD4+ T cells in the intestinal lamina propria may be important during inflammatory conditions of the gastrointestinal tract, it is necessary to fully characterize these populations in healthy individuals. Specifically, the regional variations of these lymphocyte populations within the small and large intestine may provide important clues to their function
Different regions of the intestinal tract perform diverse dietary functions and are colonized with distinct concentrations of commensal bacteria
Variable | Mean (± SD) or Frequency (%) |
Age, |
58.9±6.2 |
Sex, n (%) | |
Female | 2 (7.7) |
Male | 24 (92.3) |
Body mass index (kg/m2) | 29.3±3.3 |
Ethnicity (n, %) | |
Caucasian | 4 (15.4) |
Black | 18 (69.2) |
Hispanic | 3 (11.5) |
Other | 1 (3.8) |
Laboratory parameters | |
Hemoglobin (g/dL) | 13.7±1.4 |
Hematocrit (%) | 40.6±3.8 |
Mean corpuscular volume (fl) | 90.5±6.5 |
Blood urea nitrogen (mg/dL) | 14.8±3.8 |
Creatinine (mg/dL) | 1.01±0.1 |
Previous colonoscopies, n (%) | |
Yes | 5 (19.2) |
No | 21 (80.8) |
Variable | Mean (± SD) or Frequency (%) |
Endoscopic findings, n (%) | |
Normal | 11 (42.3) |
<3 polyps smaller than 1cm | 12 (46.2) |
≥3 polyps smaller than 1cm | 0 (0) |
Polyp(s) ≥1cm in size | 3 (11.5) |
Mass or tumor | 0 (0) |
Pathologic findings, n (%) | |
No clinically indicated biopsies taken | 12 (46.2) |
Normal mucosa or hyperplastic polyp | 6 (23.1) |
Tubular adenoma | 8 (30.7) |
Tubulovillous or villous adenoma | 0 (0) |
Any polyp with high-grade dysplasia | 0 (0) |
Carcinoma | 0 (0) |
To assess regional differences in CD4+ T helper cell populations, lamina propria mononuclear cells (LPMCs) were isolated from pinch biopsies obtained at the terminal ileum (TI), ileocecal valve (ICV), appendiceal orifice (AO), and the sigmoid colon (SC). The ICV and AO are anatomical landmarks of the most proximal portion of the large intestine (i.e. the cecum). We were particularly interested in comparing immune parameters of the cecum with the TI because it is a critical site of luminal sampling and is rich in mucosal associated lymphoid tissue
A) Representative gating strategy for the FACS analysis of lamina propria mononuclear cells from pinch biopsies obtained from four regions of healthy colonic mucosa. B) Representative FACS plots for two subjects (CAP9 and CAP24) showing IL-17+ cells (gated on CD4+ cells) from four biopsy locations in each subject. C) Cumulative data of IL-17+ CD4+ cells for all subjects. The top panel includes data from samples from all subjects with available flow cytometry data (N = 19) whereas the bottom panel shows data from subjects who have a complete set of paired samples from all four biopsy locations (N = 15). D) Representative FACS plots for two subjects (CAP9 and CAP23) showing CD25+FoxP3+ cells (gated on CD4+ cells). E) Cumulative data of CD25+FoxP3+ cells for all subjects. F) TH17/TReg ratios were plotted for all subjects according to biopsy location. Unless otherwise indicated, differences were not significant. *
Antigen | Clone | Manufacturer | Dilution | |
APC-Cy7 | CD3 | SP34-2 | BD Pharmingen | 100 |
PE-TR | CD4 | MHCD0417 | Invitrogen | 75 |
A700 | CD8 | OKT8 | eBioscience | 75 |
PerCP | CD56 | MEM-188 | Biolegend | 100 |
Pacific Blue | IFNγ | 4S.B3 | eBioscience | 100 |
A488 | IL-4 | MP4-25D2 | Invitrogen | 50 |
APC | IL-17 | eBio64CAP17 | eBioscience | 50 |
PE | IL-22 | 14292B | R&D Systems | 50 |
PECy7 | TNFα | MAb11 | BD Pharmingen | 100 |
AmCyan (AQUA) | Live/Dead | Invitrogen | 60 |
Antigen | Clone | Manufacturer | Dilution | |
APC-Cy7 | CD3 | SP34-2 | BD Pharmingen | 100 |
PE-TR | CD4 | MHCD0417 | Invitrogen | 75 |
A700 | CD8 | OKT8 | eBioscience | 75 |
PerCP | CD56 | MEM-188 | Biolegend | 100 |
Pacific Blue | IL-17 | BL168 | Biolegend | 50 |
APC | FoxP3 | PCH101 | eBioscience | 50 |
PECy7 | CD25 | M-A251 | BD Pharmingen | 50 |
AmCyan (AQUA) | Live/Dead | Invitrogen | 60 |
(A) Representative gating strategy showing total singlet, live, and IL-17+ cells from the appendiceal orifice of one patient. IL-17+ cells were further gated into either CD3− CD56− cells or CD3+CD56− cells. Approximately 80% of the CD3+ cells producing IL-17 are CD4+ lymphocytes and the remainder are mostly CD8+ lymphocytes (data not shown). (B) Plot of the total proportion of IL-17 producing cells, for all subjects, as a percentage of single, live (Aqua negative) cells. (C) Plot showing the proportion of CD3− CD56− cells that are producing IL-17. (D) Plot showing the corresponding proportion of CD3+ CD56− cells that are producing IL-17. *
To determine if there were significant non-CD4+ sources of IL-17 such as innate lymphocytes
Previous studies of mucosal biopsies from HIV infected individuals have indicated that increased frequency of TH17 cells may be accompanied by reduced frequencies of TRegs because of the developmental link between these two populations
Because it was not possible to standardize the quantity of tissue that was processed for isolating LPMCs, the results here are presented as proportional data to total CD4+ cells. Absolute cell counts could vary based on variation in the size of processed pinch biopsies. CD4+ cell viability was relatively uniform across all locations, with the exception being a slight increase in CD4+ viability from the appendiceal orifice compared to the sigmoid colon (
Terminal Ileum | Ileocecal Valve | Appendiceal Orifice | Sigmoid Colon | |
CD4+ Viability (%) | 62.0±16.6 | 71.1±7.55 | 73.4±1.98 | 61.4±11.3 |
Mean and standard deviations are shown above.
Only comparison of CD4+ viability between the appendiceal orifice and sigmoid colon was found to be statistically significant.
Recently, a population of CD4+ helper T cells that produces IL-22 but not IL-17 has been identified
A) Representative FACS plots for two subjects (CAP9 and CAP12) showing intracellular cytokine staining for IL-17 and IL-22 of lamina propria CD4+ cells. B) Cumulative data of IL-22+ IL-17− CD4+ cells for all subjects. The top panel includes data from all samples from all subjects (N = 19) whereas the bottom panel shows data from subjects (N = 15) who have a complete set of paired samples from all four biopsy locations. C) Representative FACS plots for two subjects (CAP23 and CAP26) showing staining for IL-17+FoxP3+ lamina propria CD4+ cells. D) Cumulative data of IL-17+FoxP3+CD4+ cells for all subjects. Unless otherwise indicated, differences were not significant. *
Finally, we examined the distribution of IL-17 producing TRegs, which have been reported to be elevated in the inflamed mucosa of Crohn's disease patients
Together, these results from lamina propria CD4+ T cells suggest that there may be more immune activation in the cecum compared to both the small intestine (TI) and the distal colon (SC). However, only those CD4+ cell populations that have been reported to be important for mucosal homeostasis were enriched in the cecum. When we examined TH1 and TH2 populations that produce IFNγ and IL-4, there were no significant differences among the different sites that were biopsied in this study (
A) Representative gating strategy showing IFNγ and IL-4 staining of CD4+ cells isolated from four regions of the intestine in two subjects (CAP 20 and CAP23). B) IFNγ and C) IL-4 production by CD4+ isolated from each region for all subjects. Differences between regions are not statistically significant (two tailed Mann-Whitney). TI: Terminal Ileum, ICV: Ileocecal Valve, AO: Appendiceal Orifice, SC: Sigmoid Colon.
We next analyzed the different combinations of cytokines produced by CD4+ T cell populations among different regions of the gut. We utilized Boolean gate analysis (
A) Boolean gates on IL-17, IL-22, IL-4, TNFα and IFNγ positive lamina propria CD4+ cells. Shown are representative FACS plots gated on CD4+ cells from the ileocecal valve of two subjects (CAP9 and CAP10). B) Pie charts showing the averaged pattern of cytokine production in CD4+ cells from the different regions of the gut (from N = 22 subjects). Each slice within the pie chart represents a specific combination of cytokine staining (denoted in C). Data is shown only for combinations with frequencies >2% of the total CD4+ population. IL-22+ TNFα+ IFNγ+ cells are >2% of CD4+ cells only from the ileocecal valve and appendiceal orifice. The permutation test at 10,000 permutations did not demonstrate significant differences among the pie charts represented.
To determine if the microenvironment from which we isolated lamina propria CD4+ cells may provide an explanation for the regional variation in the TH17, TH22 and TReg populations, we performed gene expression profiling experiments of paired pinch biopsies collected from the same regions that were analyzed by flow cytometry. RNA from a subset of matched samples (total N = 21, TI = 6, ICV = 5, AO = 5, SC = 5) from five subjects was isolated for DNA microarray analysis on the Agilent platform, in order to identify molecular signatures that may help to explain compositional differences in the CD4+ compartment. Unsupervised hierarchical clustering analysis was performed on 2,351 gene probes that were filtered to have a standard deviation of at least 1.0 between all 21 samples (
A) Unsupervised hierarchical clustering analysis was used to organize gene probes and samples. Each row represents an individual gene probe and each column represents an individual sample. Black indicates the median level of expression; yellow, greater then median expression; blue, less than median expression. Horizontal bars at the top of the figure indicate the dispersal of samples according to biopsy location (blue: terminal ileum; red: ileocecal valve; green: appendiceal orifice; purple: sigmoid colon). Data was filtered for probes with expressions levels that vary by a standard deviation of at least 1.0 to yield n = 2,351 unique gene probes. B) Unsupervised principal component analysis showed segregation of terminal ileum samples from colon samples along PC1 and segregation of distal (sigmoid) from proximal colon (ileocecal valve and appendiceal orifice) along PC2. C) Multiclass statistical analysis of microarrays (SAM) identified 2,079 unique gene probes that vary significantly among the sites biopsied (FDR 0%). D) Gene ontology analysis of these gene probes was performed in order to classify genes according to biological processes. Of the 2,079 unique significant gene probes, 304 were classified as relating to the immune system.
We then conducted a supervised analysis using multiclass statistical analysis of microarrays (SAM) to identify genes that were differentially expressed among regions of the intestine. 2,079 unique gene probes were identified at a False Discovery Rate (FDR) of 0% that varied significantly based on biopsy location (
We were particularly interested in the differential expression of mucin genes among different regions of the gastrointestinal tract because of their important role in mucosal barrier function
Biopsy Location | Gene Probe (Immunologic Processes Only) |
Terminal Ileum (n = 126) | CPO, PMP22, MS4A10, NTS, ABCG5, ABCG8, FBP1, ABCC2, HEBP1, DPP4, MAF, MEP1B, GSTA5, LIPA, GPX4, ENST00000377823, MSRA, SHBG, MUC3A, NLRP6, DAB1, PLB1, GSTA2, CD82, LMTK3, NPY6R, MOCOS, SEPP1, BPHL, MEP1A, CCRL1, ABCD1, CCL25, MOSC2, ABCC6, PRKAB2, ENST00000370725, SEMA6C, STAU2, CTSH, BAI2, ACSS1, TNFRSF10C, ANGPTL4, F10, CES2, TMPRSS7, CREB3L3, F11, PPARA, TNFSF15, DNAJB7, HTR4, ABCB1, ATOX1, LGALS2, HLA-DRA, NR1I3, NPNT, HLA-DMB, KLF7, ABHD6, ITGB8, JAG2, SEMA3B, TNFRSF10B, IGBP1, NCK2, GULP1, LRRC28, GPR128, PRSS7, CXCR7, CRIP1, SEMA3G, TESK2, NFATC3, RORC, CREB3L2, CD74, IFIT3, ABCG2, PLA2R1, TFPI, C8G, RAG1, LRRC66, MATN2, ERBB2IP, TMIGD1, KIR3DL2, CFB, NR1I2, TNC, ENST00000374707, ULK3, HLA-DMA, PPP1CC, CCR9, PTPRD, ADRB1, PON3, CD8B, JDP2, IRF8, PLS1, MAOA, DAPK2, CTSO, PRLR, EPHX2, PGCP, LMO4, LRRC40, TRIM32, MAP3K13, GBP3, SESTD1, CCK, PTPRH, PRKAG2, PTPRM, CD36, ABCC8, ETV7, ENST00000372411 |
Ileocecal Valve (n = 32) | ADORA2B, MOSC1, ETHE1, MB, HSF1, CTSL1, RSU1, COL8A1, CHP, PLAC8, TSPAN7, CD59, FGFR2, LGALS9C, EDA, PRDX1, NTRK2, KLK1, CLC, CCR10, F2RL1, SPR, TNFRSF17, CLIC1, PLAUR, TMPRSS4, LGALS4, FUT6, HSPG2, NLK, MFSD5, LRRC32 |
Appendiceal Orifice (n = 63) | CCL28, OASL, IER3, TSPAN1, CD9, PIGR, PPARG, FUT3, KLK3, KLHDC9, KLF8, SMAGP, LITAF, SPRYD4, IGHA2, IGHA1, LRG1, LIMK2, DRD5, TST, HSPB1, PRDX5, OSCP1, GPR39, ABCC3, C1QBP, NPY1R, ACSM3, PTGER2, FLRT3, GPR37L1, ABL1, NPY5R, LGALS9, RFXANK, ELF3, FAR2, KLK11, IGKC, ABCB11, SCAP, CPAMD8, DAO, NETO2, ABCC5, DDR1, SDC4, OAS1, CFI, AIFM3, COL9A3, MGST1, ABHD5, PLSCR1, ACSM1, ECSIT, DUSP21, RNF183, DEFB1, NCK1, PTPRA, CTSL2, GPR110 |
Sigmoid Colon (n = 83) | TFCP2L1, MUC1, LRFN4, EHF, VSIG2, CKB, SELENBP1, GPX2, CFTR, EPHA4, PNKD, EFEMP1, LRRN2, PRDX6, CAMK1D, GLIPR2, IL1R2, PPY, PPIF, GHR, SCARA5, FBLN2, IGFALS, NOX1, TK1, EPHB2, PTGDR, CFD, IGLC3, THBS1, CLIC4, CD14, TIMD4, IGF1R, ROR1, MUC5B, TRIO, GPR125, EPOR, PTPRU, C1QTNF6, ENST00000453184, GPR161, KLHDC4, NOTCH2, CFH, CFHR3, IGLL1, ENST00000390247, HSP90B1, EPHA3, KLK15, ENST00000390243, SEMA3F, NFASC, BATF2, ACR, CTSC, DCN, CDK4, IL1F7, PPIH, S100A10, DCBLD2, FKBP11, IGJ, CD81, FBLN1, PRDX4, LAMA2, RABEPK, CRYAB, FN1, STIL, NTRK3, LRIG3, SLIT3, TNFAIP6, ITPR2, FKBP9, SCRIB, RAD51, HSP90AB2P |
We also explored the differential expression of the peroxisome proliferator-activated receptor (PPAR) members of the nuclear hormone receptor superfamily because they are important regulators of inflammation
Expression levels of selected genes were measured in 40 intestinal biopsy samples from the terminal ileum (TI), ileocecal valve (ICV), appendiceal orifice (AO), and sigmoid colon (SC) and normalized to glyceraldehyde-3 dehydrogenase (GAPDH) transcript levels. Values were log transformed as shown. Horizontal bars indicate median expression levels. Statistical significance between groups was determined by two-tailed Mann Whitney test. *
A) 347 gene probes were significantly elevated in the cecum relative to the sigmoid colon, 47 of which were involved in immunologic processes as determined by gene ontology analysis. 160 gene probes were significantly enriched in the sigmoid colon compared to the cecum, 35 of which were involved in immunologic processes. Genes probes related to immunologic processes are shown in the table below the figure. Analyses shown were performed at a FDR of 0%. B) Verification of gene expression by real-time PCR analysis of PPARA, PPARG, and MUC1 normalized to GAPDH transcript levels in 40 intestinal biopsy samples. Values were log transformed as shown. Horizontal bars indicate median expression levels. Statistical significance between groups was determined by two-tailed Mann Whitney tests. *
Consistent with the hypothesis that there is more bacterial mediated activation in the cecum, we confirmed elevated expression of the anti-microbial peptide DEFB1 (
Real-time PCR analysis of bacterial ribosomal 16S DNA sequences with primers specific for universal bacterial 16S,
Having generated a combination of flow cytometry and transcriptional profiling datasets from paired biopsy samples, we sought to identify genes that have expression levels that are directly correlated with the frequency of lamina propria TH17 cells and TRegs in these healthy individuals (
(A) The frequency of TH17 cells was used as a quantitative variable to identify gene probes with correlated expression values using significance analysis of microarrays (SAM). Gene probes in red are positively correlated and gene probes in green are negatively correlated with TH17 cell frequency at a FDR of 0%. (B) Identification of gene probes correlated with frequency of CD4+CD25+FoxP3+ TReg cells. C) Real time PCR analysis of 40 biopsy samples confirms the positive correlation between TH17 cells with RETN expression, the negative correlation between TH17 cells with TFF1 expression, and the positive correlation between TReg cells with FCRL5 expression.
Cell Population | Positively Correlated Gene Probes | Negatively Correlated Gene Probes |
TH17 (CD4+ IL-17+) | A_33_P3246244, FLJ38028, CELA3A, RETN | TFF1, lincRNA:chr3:195418384-195419180_F, lincRNA:chr3:195435000-195435680_F, lincRNA:chrX:73164173-73167168_F, HLA-DQB1, lincRNA:chrX:73164183-73214799_F, lincRNA:chrX:73164176-73167153_F, lincRNA:chrX:73164675-73232924_R, hg18:lincRNA:chr3:196920803-196924230_F, lincRNA:chr3:195436978-195437762_F, LOC729668, MXD1 |
TRegs (CD4+ CD25+ FoxP3+) | CNR1, FCRL5, PRKD3, ZNF10, CD38, BCL2, lincRNA:chr2:157192429-157198954_R, ZDHHC2, UNC119B, ZNF783, TRAF5, ADAM28, LOC729678, CHD6, NCRNA00120, LDLRAD2, ARID5B, DAPL1, LOC100130298, NIN, KLF12, SUGT1L1 |
In this study, we have systematically characterized regional differences of intestinal lamina propria CD4+ T cell populations by flow cytometry in a healthy population and identified gene expression patterns that correlate with their frequencies. We found the cecum to have significantly elevated frequencies of TH17, TH22, and TReg lymphocyte populations (but not TH1 or TH2 cells). Interestingly, these are the CD4+ subsets that are most important in regulating intestinal homeostasis. While TH17 cells are enriched in the terminal ileum in mice, we find here that the human cecum has a higher frequency of TH17 cells than does the ileum, reflecting important differences between mice and humans. Since intestinal mucosal CD4+ T cells are being increasingly studied under disease conditions (e.g. inflammatory bowel disease and HIV), it is important to rigorously investigate the baseline mucosal immune environment throughout the gut in healthy individuals. When mucosal biopsies are collected from different parts of the human intestine, there must be an awareness that inherent regional differences among CD4+ T cell populations are present in order to interpret study findings.
The results of our study are consistent with a previous histopathology study showing that the cecum is a site of inherent inflammation even in a normal healthy population without gastrointestinal symptoms
The cecum is generally considered to play a digestive role, being enlarged in herbivores to aid in the breakdown of cellulose
Recently, innate lymphoid cells (ILCs) have emerged as an important non-CD4+ source of effector cytokines that may be particularly important at mucosal barrier surfaces
We attempted to determine if the biopsies collected from the cecum had a greater bacterial load attached to the intestinal wall compared with those obtained from the terminal ileum and the sigmoid colon, but no significant differences were observed based on qPCR analysis of several bacterial ribosomal 16S DNA sequences (relative to host DNA). It is certainly conceivable that a deep sequencing analysis of bacterial ribosomal 16S units may lead to the identification of novel bacterial species or operational taxonomic units (OTUs) that are more abundant on the cecal wall compared to other parts of the intestine. Micro-heterogeneity between sample sites has been reported based on the very limited number of individuals who have been evaluated by deep sequencing studies of the colonic mucosa
In a previous human study, gene expression profiling analysis was performed along the entire proximal-distal axis of the colon, but the terminal ileum was not included
By correlating our flow cytometry analysis with gene expression profiling data from paired biopsy samples we discovered a positive relationship between the expression of resistin (RETN) and the frequency of TH17 cells. Resistin is a cytokine produced by adipose tissue and was originally discovered as a potential mediator of metabolic functions involved in insulin resistance
We also found a negative relationship between the frequency of TH17 cells and the expression levels of TFF1. The trefoil factors are mucin-associated peptides associated with a number of human tissues, with TFF1 and TFF2 primarily located in the gastric mucosa and TFF3 predominantly present in the mucus cells of the small and large intestine
Finally, we found that TReg frequencies were positively associated with expression of FCRL5 (CD307). FCRL3, a closely related FCRL family member, is highly expressed on dysfunctional TRegs that express high levels of PD-1 and have a memory phenotype
This study has important limitations. The majority of the enrolled subjects were older black men and so their mucosal environment may not be representative of younger patients in a disease state. Furthermore, complete colonoscopies requiring a preparative purge were performed to obtain biopsies from the cecum, a feature that may impact the analysis of the intestinal microenvironment. While the pinch biopsy samples obtained were approximately equal in size from all locations and from all subjects, we did not directly measure the absolute numbers of cells per gram of pinch biopsy tissue from each location. Importantly, CD4+ viability was relatively similar independent of biopsy location. Lastly, we recognize that differences in gene expression profiles of the pinch biopsies may be caused by heterogeneity of cellular populations and cellular density between samples. Nonetheless, this study is a step towards understanding location-specific variations in lamina propria CD4+ T cell populations in healthy individuals. This information may provide a basis for comparison when characterizing disease conditions that have characteristic distribution patterns along the intestinal tract, such as Crohn's disease and ulcerative colitis.
New York Harbor Veterans Affairs Hospital Institutional Review Board approval was obtained before enrolling subjects in the study. Written informed consent was received from all participants.
Consecutive subjects over the age of 50 who were at an average risk for colon cancer presented for screening colonoscopy and were enrolled in the study. Subjects were excluded who required endoscopy for an indication other than screening (e.g. family history of colon cancer, iron deficiency anemia, or hematochezia), were positive for human immunodeficiency virus (HIV), or who had absolute or relative contraindications to acquisition of biopsies for research purposes at the time of colonoscopy (e.g. systemic anticoagulation at the time of the procedure).
Six to eight pinch biopsies were obtained at colonoscopy from the terminal ileum (TI), the ileocecal valve (ICV), the appendiceal orifice (AO), and the sigmoid colon defined as 20 centimeters from the anal verge (SC) using sterile cold biopsy forceps. Not every location was biopsied in all subjects due to technical factors (e.g. a tortuous colon did not permit terminal ileum intubation). The mucosa was directly observed and irrigated after biopsy acquisition to ensure resolution of bleeding. One biopsy from each location was snap-frozen for RNA extraction in Trizol reagent (Invitrogen). The remaining biopsies were placed in complete RPMI containing 10% fetal calf serum, 0.05 mM 2-Mercaptoethanol, and penicillin/streptomycin/glutamine (Invitrogen).
Biopsies were digested at 37°C for 1 hour in 100units/mL of collagenase Type VIII (Sigma) and 150 μg/mL DNase (Sigma) in complete RPMI. Cells were filtered through a 50 micron filter, washed with 5 mL 1X PBS, and pelleted. Cells were then resuspended in 40% Percoll (GE Healthcare), under-layered with 80% Percoll, and centrifuged at 2,200 rpm for 20 minutes at room temperature. Mononuclear cells were collected at the interface and used for subsequent flow cytometric analyses.
Cells were stimulated with phorbol 12- myristate 13-acetate (PMA) and ionomycin for 4 hours at 37°C in the presence of brefeldin A (GolgiPlug, BD). Cells were subsequently divided for staining in one of two panels: (1) a “cytokine” panel whereby cells were stained with anti-CD3, anti-CD4, anti-CD8, and anti-CD56 and fixed in 4% paraformaldehyde in PBS and (2) a “nuclear antigen” panel whereby cells were stained with anti-CD3, anti-CD4, anti-CD8, anti-CD56, and anti-CD25 surface markers using the Fix/Perm Buffer Kit (eBioscience) for fixation and permeabilization. Live/Dead (aqua) viability dye (Invitrogen) was added to each panel. Cells in the “cytokine” panel were permeabilized and stained with an intracellular cytokine panel for interleukin (IL)-4, IL-17, IL-22, interferon-γ (IFNγ), and tumor necrosis factor-α (TNFα); cells in the “nuclear antigen” panel were stained with forkhead box P3 (FoxP3). Simultaneous multi-color flow cytometry was performed (BD LSR II). Results were analyzed in Flowjo (Treestar, Inc.) and statistical analysis was performed using Prism (GraphPad Software, Inc.)
Five cytokine-producing CD4+ cell populations were analyzed in Flowjo using Boolean gates in order to calculate 32 possible cytokine populations. Data was exported to Simplified Presentation of Incredibly Complex Evaluations (SPICE) and filtered at a 2% cutoff to simplify the representation of the data (
DNA was isolated from intestinal pinch biopsies stored in Trizol using the DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer's instructions. After a chloroform purification and ethanol extraction step, DNA was probed with Taqman probes designed for bacterial genes of interest (Applied Biosystems). Bacterial probes were selected for universal bacteria 16S, Clostridiales, Bacteroides, Prevotella, and Fusobacterium as previously described
Complementary DNA (cDNA) was reverse transcribed from RNA isolated from intestinal pinch biopsies according to manufacturer's instructions (Agilent Technologies). Cyanine 3-labeled, linearly amplified complementary RNA (cRNA) was then synthesized, purified, hybridized to microarray slides, and scanned using the High Resolution C Scanner according to the manufacturer's instructions (Agilent Technologies). The raw data was then uploaded to Microsoft Excel, where it was log-transformed quantile-normalized and median centered. Expression profiling data were filtered at a standard deviation of 1.0 before undergoing unsupervised hierarchical clustering analysis in Cluster (Eisenlab). Results were then visualized with Java Treeview. Principal component analysis (PCA) was performed on the gene expression parameters using Cluster to generate eigenvalues, and the resulting datasets were further compiled and plotted on Excel. Filtered data sets were also analyzed for statistically significant genes (either through unpaired two-way comparison or multiclass analysis) with the Statistical Analysis of Microarrays (SAM) software version 2.23 A (
1μg of RNA from each sample was reverse-transcribed using SuperScript III Reverse Transcriptase (Invitrogen) and the resulting cDNA was used for quantitative real-time PCR with Taqman probes ordered directly from the manufacturer for the following genes of interest: DEFB1 (Hs00608345_m1), FCRL5 (Hs01070204_m1), MUC1 (Hs00159357_m1), MUC3 (Hs03649367_mH), MUC5 (Hs00861588_m1), PPARA (Hs00947539_m1), PPARG (Hs01115513_m1), TFF1 (Hs00907239_m1), and RETN (Hs00220767_m1) (Applied Biosystems). All cycle threshold values were normalized to GAPDH values. No significant differences in GAPDH expression were observed among the biopsy sites (data not shown). Data was analyzed with the t test using Prism 5.0 (GraphPad Software).
Statistical analysis was performed using Prism 5.0 (GraphPad Software). The two-tailed Mann Whitney non-parametric t test was used to assess statistical significance for all samples.
We acknowledge the patients who graciously participated in this study and the medical staff of the New York Harbor Veterans Affairs Hospital who assisted in the execution of the biopsy protocol. We thank Charlie Kim, Ph.D. in the Division of Experimental Medicine at the University of California, San Francisco for his expert assistance with the microarray analysis. We thank Martin Blaser, M.D. and Dan Littman, M.D. at the New York University School of Medicine for their suggestions throughout this project.