Analysis of Flagellin-Specific Adaptive Immunity Reveals Links to Dysbiosis in Patients With Inflammatory Bowel Disease

Abstract

Background & aims: Bacterial flagellin is an important antigen in inflammatory bowel disease, but the role of flagellin-specific CD4⁺ T cells in disease pathogenesis remains unclear. Also unknown is how changes in intestinal microbiome intersect with those in microbiota-specific CD4⁺ T cells. We aimed to quantify and characterize flagellin-specific CD4⁺ T cells in Crohn's disease (CD) and ulcerative colitis (UC) patients and study their relationship with intestinal microbiome diversity.

Methods: Blood was collected from 3 cohorts that included CD patients, UC patients, and healthy controls. Flow cytometry analyzed CD4⁺ T cells specific for Lachnospiraceae-derived A4-Fla2 and Escherichia coli H18 FliC flagellins, or control vaccine antigens. Serum antiflagellin IgG and IgA antibodies were detected by enzyme-linked immunosorbent assay and stool samples were collected and subjected to 16S ribosomal DNA sequencing.

Results: Compared with healthy controls, CD and UC patients had lower frequencies of vaccine-antigen-specific CD4⁺ T cells and, as a proportion of vaccine-specific cells, higher frequencies of flagellin-specific CD4⁺ T cells. The proportion of flagellin-specific CD4⁺ T cells that were CXCR3^negCCR4⁺CCR6⁺ Th17 cells was reduced in CD and UC patients, with increased proportions of CD39⁺, PD-1⁺, and integrin β7⁺ cells. Microbiome analysis showed differentially abundant bacterial species in patient groups that correlated with immune responses to flagellin.

Conclusions: Both CD and UC patients have relative increases in the proportion of circulating Fla2-specific CD4⁺ T cells, which may be associated with changes in the intestinal microbiome. Evidence that the phenotype of these cells strongly correlate with disease severity provides insight into the potential roles of flagellin-specific CD4⁺ T cells in inflammatory bowel disease.

Keywords: CD4(+) T Cells; Crohn’s Disease; Microbiome; Ulcerative Colitis.

Graphical abstract

Figure 1

Flagellin-specific CD4⁺T cells can be detected in IBD patients’ peripheral blood. (A) Gating strategy and representative flow cytometry data for cohort 1. (B) The percentage of CD25⁺OX40⁺ cells within CD4⁺ T cells after stimulation of whole blood with FliC or Fla2 for 44 hours (CD, n = 55; UC, n = 7). (C) Anti-FliC and anti-Fla2 IgG levels in plasma measured using an enzyme-linked immunosorbent assay (ELISA); concentrations are in arbitrary units based on high-titer pooled plasma standards. (D) Correlations between FliC– and Fla2–specific CD4⁺ T cells and IgG levels and (E) correlations between FliC- and Fla2-specific CD4⁺ T cells and IgG levels. FliC- and Fla2-specific CD4⁺ T-cell responses were compared between CD patients based on (F) current treatments (untreated, n = 5; glucocorticoids or mesalamine, (n = 9 for FliC and n = 8 for Fla2); Fla2, antimetabolites n = 26 and biologics n = 19) and (G) clinical phenotype of disease: perianal (n = 5), luminal (n = 20), or stricturing/penetrating (n = 9). Statistical analyses used (B and C) Mann–Whitney U tests, (D and E) calculated Spearman Rho (r), and (F and G) Kruskal–Wallis tests. APC, allophycocyanin; PECy7, phycoerythrin-cyanine 7.

Figure 2

Flagellin-specific immune responses in CD patients before and after anti-TNFα therapy. OX40 assays were performed for cohort 2 (n = 14 CD patients), before anti-TNFα treatment, and at 8 and 24 weeks after treatment. For each individual, data are shown for (A) the proportion of FliC- and Fla2-specific CD4⁺ T cells (n = 14 at weeks 0 and 8, n = 13 at week 24) and (B) the proportion of Pediacel-specific CD4⁺ T cells (n = 12 at weeks 0 and 24 and n = 11 at week 8). (C) FliC- and Fla2-specific CD4⁺ T cells are shown as a percentage of Pediacel-specific CD4⁺ T cells (n = 12 at weeks 0 and 24 and n = 11 at week 8). (D) Anti-FliC and anti-Fla2 IgG and IgA levels were measured by enzyme-linked immunosorbent assay at each time point (n = 12). Statistical analysis used Wilcoxon signed-rank tests. Spearman Rho (r) correlations between anti-FliC and anti-Fla2 (E) IgG and IgA levels from all time points (n = 11, each at 3 time points); and (F) OX40 assay responses and IgG and IgA levels.

Figure 3

Flagellin-specific CD4⁺T cells are enriched proportionally in IBD patients. (A) Gating strategy and representative flow cytometry data for cohort 3 for all antigens tested (n = 20 each for healthy controls, CD patients, and UC patients). The percentage of CD25⁺OX40⁺ cells within CD4⁺ T cells after stimulation of whole blood for 44 hours with (B) SEB or Pediacel, or (C) FliC or Fla2 antigens. (D) Anti-FliC and anti-Fla2 for subjects with detectable (>0.02% of CD4⁺ T cells) Pediacel-specific CD4⁺ T cells (n = 19 healthy, n = 17 CD, n = 18 UC), the proportions of FliC- and Fla2-specific T cells were analyzed as a proportion of Pediacel-specific CD4⁺ T cells within each individual (Kruskal–Wallis test). PE, phycoerythrin.

Figure 4

Age and disease severity correlations with flagellin-specific immune responses. (A) IgG levels and (B) IgA levels (n = 20 for all groups) were measured by enzyme-linked immunosorbent assay. Correlation analyses of combined healthy controls, CD patients, and UC patients (n = 60, cohort 3) between age at time of blood collection and (C) OX40 responses to SEB, Pediacel, FliC, and Fla2, and (D) levels of anti-FliC and anti-Fla2 IgG and IgA. (E) Correlation analyses of CD and UC patients from cohort 3 (n = 40) between Harvey–Bradshaw Index (reported at time of blood collection) and OX40 responses to FliC and Fla2. Correlation analyses were calculated using Spearman rho (r).

Figure 5

Gating strategy for phenotypic analysis of flagellin-specific CD4⁺T cells. (A) Gating strategy for phenotype analysis of antigen-specific CD4⁺ T cells in cohort 3. (B) Gates for CCR4, CCR6, CXCR3, gut homing marker integrin β7, and the co-inhibitory marker PD-1 were set using CD3^neg cells. Gates for CD39 (to identify a T regulatory (Treg)-enriched cell population) were set using lymphocytes. APC, allophycocyanin; FITC, fluorescein isothiocyanate; PECy7, phycoerythrin-cyanine 7.

Figure 6

IBD patients have reduced proportions of flagellin-specific CD4⁺T cells with a Th17 cell surface phenotype. (A) Data from all subjects in cohort 3 (n = 20 each of healthy controls, CD patients, and UC patients) were combined to assess differences in Th1, Th17, and Th17.1 cell proportions within CD4⁺ T-cell responses to SEB, Pediacel, FliC, and Fla2 antigens (pie charts show mean responses). (B) Data in panel A were analyzed to determine differences between healthy controls (Healthy), CD patients, and UC patients for the proportions of Th1, Th2, Th17, and Th17.1 cells within all antigen-specific CD4⁺ T-cell responses measured. (C) Unstimulated whole blood for cohort 3 (n = 20 each for healthy controls, CD patients, and UC patients) was analyzed for the frequency of CD4⁺ T cells (percentage of lymphocytes, n = 20 each) and Th1, Th17, and Th17.1 cells (percentage of CD4⁺ cells). Statistical tests used were as follows: (A) Friedman test and (B and C) Kruskal–Wallis test; the n for analysis of each parameter not specified here is provided in Table 5. Ag, antigen.

Figure 7

Flagellin-specific gut homing and regulatory CD4⁺T-cell populations are enriched in IBD patients. (A) For cohort 3, differences were assessed between groups for the proportions of PD-1⁺ cells and integrin β7⁺PD-1⁺ cells within FliC- or Fla2-specific CD4⁺ T-cell responses. (B) Correlation analysis between the Harvey–Bradshaw Index and the proportion of FliC-specific (n = 21) and Fla2-specific (n = 16) CD4⁺ T cells that were integrin β7⁺PD-1⁺. (C) tSNE plots of concatenated Fla2-specific responses, with a gated CD39⁺CCD6^neg cell population identified by FlowSOM clustering analysis. The CD39⁺CCD6^neg cell population gate and frequency are shown for concatenated Fla2-specific responses. (D) Proportions of CD39⁺CCD6^neg cells within Fla2-specific (n = 12 HC, n = 10 CD, and n = 17 UC) and FliC-specific (n = 18 HC, n = 13 CD, and n = 19 UC) responses. (E) Spearman rho correlation between frequency of Fla2-specific (n = 27) or FliC-specific (n = 32) CD4⁺ T cells and the Harvey–Bradshaw Index. The n for analysis of each parameter in panels A and D is shown in Table 5. (A, C, D, and F) The Kruskal–Wallis test was used. Ag, antigen; FITC, fluorescein isothiocyanate.

Figure 8

Correlation of fecal microbiome composition with antiflagellin immune responses. (A) Nonmetric multidimensional scaling (MDS1 and MDS2) ordination plot from analysis of β-diversity within 16S rDNA samples for healthy controls, CD patients, and UC patients in cohort 3 (n = 13 each). Adonis multivariate analysis identified that both UC and CD patient groups clustered significantly distinctly from healthy controls (P = .035). Bacteria are shown that were significantly differently abundant in (B) CD patients and (C) UC patients compared with healthy controls. (B and C) Multiple dots indicate detection of >1 sequence for the bacterial genus. (D) Comparison of Shannon’s diversity (H’) index between groups (Kruskal–Wallis test). Spearman (r) correlation between Shannon’s diversity (H’) index and (E) immune responses in patients and healthy controls (n = 39) and (F) Harvey–Bradshaw index for UC and CD patients (n = 26). (G) Heat map showing Spearman correlation analyses between the relative abundance of differentially expressed bacteria and antiflagellin immune responses.

Figure 9

Phylogenetic clustering of bacterial species based on FliC/Fla2 16S rDNA homology. Phylogenetic tree of bacteria closely related by 16S rDNA sequence to E coli strain 118UI, the source of FliC, and Lachnospiraceae bacterium A4, the source of Fla2. Enlarged portions of the tree are shown for bacteria with >87% homology to these strains.