Class Ib MHC–Mediated Immune Interactions Play a Critical Role in Maintaining Mucosal Homeostasis in the Mammalian Large Intestine

TCRαβ⁺CD8⁺ T cell niche in colonic IEL is different from other mucosal compartments in steady state

To gain a better understanding of steady-state composition of TCRαβ⁺CD8⁺ T cells, we first analyzed the presence of innate-like TCRαβ⁺CD4⁻B220⁻CD8αα⁺ T cells and their adaptive counterpart TCRαβ⁺CD4⁻B220⁻CD8αβ⁺ T cells in different gut mucosal compartments: colon IEL and LP fractions, small intestinal IEL, and MLN from naive B6 mice. We found that the frequency of TCRαβ⁺CD8αα⁺ T cells in colonic IEL (as compared with other compartments) was much higher than that of CD8αβ⁺ T cells (Fig. 1A). Next, we determined whether the cell surface phenotype of TCRαβ⁺CD8αα⁺ cells is similar to that displayed by regulatory CD8⁺ T cells. We found that the TCRαβ⁺CD8αα⁺ T cell population among the colon IEL expresses two markers, CD44 and the NK inhibitory receptors Ly49CIFH, whereas the expression of CD122 is low/no. In contrast, neither the TCRαβ⁺CD8αα T cells in colon LP nor CD8αβ⁺ T cells in colonic IEL or colon LP express Ly49CIFH (Fig 1B). Consistent with their regulatory phenotype, colonic TCRαβ⁺CD8αα⁺ T cells predominantly were Helios⁺Foxp3⁻ in the colon IEL fraction in comparison with the colon LP cells (Supplemental Fig. 1A). Similar to the unique niche of CD8⁺ T cells in murine colonic IEL, in silico analysis of CD8⁺ cells in the epithelial layer versus LP in healthy human colon also revealed a differential gene expression profile underlining the uniqueness that intraepithelial residence provides to these lymphocytes in the steady state (Supplemental Fig. 1B). Our murine data indicate a unique phenotype of the colon IEL TCRαβ⁺CD8αα⁺ T cells containing potential regulatory CD8⁺ populations in the steady state in naive B6 mice.

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FIGURE 1.

In steady state, colonic IEL harbors a rich proportion of TCRαβ⁺CD8αα⁺ T cell subsets

(A) Representative images from three independent experiments, showing comparative frequency of TCRαβ⁺CD4⁻B220⁻CD8αα⁺ and TCRαβ⁺CD4⁻B220⁻CD8αβ⁺ T cells in colonic IEL, colonic LP, small intestinal IEL, and MLN from WT B6 female mice (n = 4–5). Gates on each flow plot indicate percentage of CD8αα⁺ (left one) and CD8αβ⁺ (right one) T cells in each tissue. (B) CD8αα⁺ T cells in colonic IEL express NK inhibitory receptors. Gates in the contour plots (upper panels) indicate CD44⁺CD122^lo/− events in CD8αα⁺ (left panel) or CD8αβ⁺ (right panel) T cells for colonic IEL or colonic LP as indicated. Gates in the density plots (lower panels) indicate Ly49CIFH⁺ events within the selected gating. Bar graph represents quantification of percentage of Ly49CIFH⁺CD44⁺ CD122^lo/− cells in the four cell populations. Each dot in the bar graph represent one animal. Data are representative of two independent experiments. Error bars represent mean ± SEM. A student t test was used to determine statistical significance. Co-IEL, colonic IEL; Co-LP, colonic LP; SI-IEL, small intestinal IEL. **p < 0.01.

Colonic IEL TCRαβ⁺CD8αα⁺ and CD8αβ⁺ T cells correlate differentially with induction and restoration phases in an acute model of colitis

Next, we determined the dynamics of different TCRαβ⁺CD8⁺ T cell subsets during acute inflammation in the colon. We used body weight loss as a general disease parameter in an acute model of DSS colitis. Mice started to lose body weight on day 5 after initiation of DSS (2.5%), with the peak of weight loss occurring on day 9 and subsequent weight gain (Fig. 2A). We found that the percentages of TCRαβ⁺CD8αα⁺ but not CD8αβ⁺ T cells in the colon IEL were markedly decreased during the peak disease phase (Fig. 2B, 2C). In contrast, their percentage in the LP was not significantly affected under these conditions. In comparison, TCRαβ⁺CD8αβ⁺ T cells increased by 10-fold among the colon IELs during the most severe phase of the disease, whereas CD4 T cells increased later in the recovery phase (Fig. 2C). In the LP fraction, we could only observe an increase in CD4⁺ T cells during the restoration phase (Fig. 2D). Thus, a significant increase in TCRαβ⁺CD8αβ⁺ T cells in the colon IEL during inflammation suggests that they might contribute to disease, whereas a significant decrease in TCRαβ⁺CD8αα⁺ T cells is consistent with a regulatory role. The quantification of absolute cell numbers also concurred with a significant accumulation of TCRαβ⁺CD8αβ⁺ T cells (Fig. 2E). Although the decrease in TCRαβ⁺CD8αα⁺ T cells was not significant, their increase was significant during the restoration phase (Fig. 2E). In addition, an enhancement in CD4 T cell numbers in IEL and LP was observed, but no significant alterations were found in CD8⁺ T cell subset numbers in LP (Fig. 2E, 2F).

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FIGURE 2.

TCRαβ⁺CD8⁺ T cell subsets in colonic IEL are a marker of pathology and restitution in an acute model of colitis

(A) Body weight loss curve in acute DSS colitis. WT B6 mice (n = 3–5 per group) were fed 2.5% DSS (or not for vehicle controls) in water for 7 d and then switched to regular water. (B) Representative Flow plots showing CD45+ TCRαβ⁺CD4⁻B220⁻ events on different days in the acute DSS colitis. CD8αα⁺ T cells (top left gate in each plot) correlate negatively with induction and positively with restoration phases in an acute model of colitis in contrast to CD8αβ⁺ (top right gate in each plot) T cells. (C) Scattered plots indicate percentage of CD8αα⁺ (left panel), CD8αβ⁺ (middle panel), and CD4⁺ (right panel) in CD45⁺ TCRαβ⁺CD4⁻B220⁻ T cells from colonic IEL. Each dot represents one animal. (D) Scattered plots indicate percentage of CD8αα⁺ (left panel), CD8αβ⁺ (middle panel), and CD4⁺ (right panel) in CD45⁺ TCRαβ⁺CD4⁻B220⁻ T cells from colonic LP. (E and F) Absolute cell numbers for T cell subsets shown in (C) and (D) calculated using live-gated events extrapolated by total cell numbers using the trypan blue method. Each dot represents one animal. Data are representative of three independent experiments. Error bars represent mean ± SEM. One-way ANOVA was used to determine statistical significance. Co-IEL, colonic IEL; Co-LP, colonic LP. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Administration of an agonistic peptide for the TCRαβ⁺CD8αα⁺ T cells protects colitis in WT mice but not in Qa-1b^−/− mice

We have recently identified an agonistic 9-mer peptide that stimulates Qa-1 restricted regulatory TCRαβ⁺CD8αα⁺ T cells in vitro and in vivo and protects mice from EAE (H. Sheng, I. Marrero, I. Maricic, and V. Kumar, manuscript in preparation). Since TCRαβ⁺CD8αα⁺ T cells are decreased during colitis, we wanted to investigate whether prophylactic in vivo stimulation of these T cells with the agonistic peptide would confer protection in the acute model of colitis. Accordingly, we found that the administration of the agonistic peptide in WT B6 mice resulted in a significant reduction in gross colon parameters and cumulative colitis scores on the day of peak body weight loss (Fig. 3A, 3B). Explant cultures from peptide-treated mice also showed significant reduction in proinflammatory cytokine production (Fig. 3C). Although we observed that the peptide-treated mice gained weight after DSS treatment, we found that this weight gain was due to the IFA used to emulsify the peptide, and, therefore, in IFA-only controls, body weight was enhanced but without any effect on other colonic disease parameters (Supplemental Fig. 2A, 2B). To avoid this confounding variable, for further experiments with the peptide, we omitted body weight loss as a disease parameter and focused instead on other disease parameters to measure colitis. Next, to determine whether the peptide-mediated protection is Qa-1–dependent, we administered peptide in mice deficient in Qa-1b. In contrast to WT mice, peptide treatment failed to provide protection in Qa-1b^−/− mice as observed by gross colonic parameters and cytokines in explant cultures (Fig. 3D–F). These data indicate that the protection from colitis induced following peptide treatment is Qa-1^b–dependent.

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FIGURE 3.

Peptide-mediated protection from colitis is Qa-1b–dependent

(A) Representative photographs, from three independent experiments, showing colons from control-treated (P−, upper panel) or peptide-treated (P+, lower panel) WT B6 mice (n = 4–7) from acute DSS colitis model. (B) Bar graph showing cumulative colitis scores of control- or peptide-treated WT B6 mice from acute DSS colitis model. Each dot represents one animal. Error bars represent mean ± SEM. Non-parametric (Mann–Whitney) test was used to determine statistical significance. ****p < 0.0001. (C) Bar graphs showing concentration (pg/ml) values from CBA kit analysis of cytokines (TNF-α, IL-6, IFN-γ, IL-17A, and IL-10) released in supernatant from colon explant culture. Colons were from control- or peptide-treated WT B6 mice from acute DSS colitis model. A Student’s t test was used to determine statistical significance. *p < 0.05, **p < 0.01, ***p < 0.001. (D) Representative photographs showing colons from control-treated (P−, upper panel) or peptide-treated (P+, lower panel) Qa-1b^−/− mice from acute DSS colitis model. (E) Bar graph showing cumulative colitis scores (without histological scores) of control- or peptide-treated Qa-1b^−/− mice from acute DSS colitis model. (F) Bar graphs showing concentration (pg/ml) values from CBA kit analysis of cytokines (TNF-α, IL-6, IFN-γ, IL-17A, and IL-10) released in supernatant from colon explant culture. Colons were from control- or peptide-treated Qa-1b^−/− mice from acute DSS colitis model. Each dot represents one animal. Error bars represent mean ± SEM.

CD103⁺CD11b⁻ cDCs populate colonic IEL during peak of DSS-induced colitis and uniquely upregulate Qa-1^b

We have previously demonstrated that DC-mediated Ag cross-presentation is required to induce TCRαβ⁺CD8αα⁺ T cells and facilitate their immunoregulatory function in EAE (34). There are several well-known subsets of professional APCs in mammalian intestine, and some of them have been implicated in immunoregulation (35–37). Of these subsets, cDC1s, characterized as CD103⁺CD11b⁻ in the murine intestine, are also known to display enhanced Ag cross-presentation properties in several situations (38, 39). Recently, intestinal cDC1s in mice have been reported to maintain tolerance to epithelial Ags involving a Foxp3⁺CD8⁺ Treg-inducing mechanism (40). As a first step toward determining whether DCs play a role in mediating the anti-inflammatory functions of CD8αα⁺ T cells, we characterized the phenotypes of DCs in the intraepithelial compartment, where TCRαβ⁺CD8αα⁺ T cells mainly reside, during colitis. We found a significant increase in the percentage of several DC subsets in the IEL fraction, including DCs that are barely present in the IEL fraction in the steady state, such as CD103⁺CD11b⁻ cDCs, but they were mostly found in the LP fraction. Additionally, DCs that we found to be present in the steady-state IEL included plasmacytoid DCs (pDCs) and CD103⁻CD11b⁺ cDCs (Fig. 4A, 4B, Supplemental Fig. 2C). Thus, we found that CD103⁺CD11b⁻ cDCs (cDC1s), but not pDCs or CD103⁻CD11b⁺ cDCs (cDC2s), significantly decreased, by frequency and numbers, among colon IEL after day 8, which correlated with the change in TCRαβ⁺CD8⁺ T cells at that time. Based on absolute numbers, we also found a general increase in both LP and IEL on day 16 compared with other days (Supplemental Fig. 2C). Next, we determined the expression of Qa-1b among various DC subsets and macrophages during colitis in colon IEL from WT mice. Analysis of the surface levels (geometric mean fluorescence intensity) of Qa-1b revealed that CD103⁺CD11b⁻ cDCs in colon IEL are the major Qa-1b–expressing DC population (Fig. 4C, 4D). Thus, a significant correlation between the numeric changes in Qa-1b⁺ CD103⁺CD11b⁻ cells and in the relevant subsets of TCRαβ⁺CD8⁺ T cells suggests that cDC1s may be important for the peptide-mediated Qa-1b–dependent protection from colitis.

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FIGURE 4.

Batf3-dependent CD103⁺CD11b⁻ cDCs accumulate in colonic IEL and are enriched in Qa-1b expression

(A) Representative flow plots from two independent experiments, showing CD45⁺MHC class II⁺CD3⁻CD19⁻CD11c⁺CD11b⁻CD103⁺ cDC events (bottom right quadrant) in colonic IEL on different days in acute DSS colitis in B6 mice (n = 3–5 per group). (B) Scattered plot showing percentage (left panel) of CD11b⁻CD103⁺ cDCs in CD45⁺MHC class II⁺CD3⁻CD19⁻CD11c⁺ cells and absolute numbers (right panel) in colonic IEL. One-way ANOVA was used to determine statistical significance. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. (C) Bar graph showing ratio of geometric mean fluorescence intensity (GMFI) for Qa-1b expression over fluorescence minus one control for each myeloid cell population (macrophages [Macs] and DCs) in colon (IEL or LP) with or without inflammation on day 8 of acute DSS colitis model. (D) Representative histogram overlay for Qa-1b expression on CD103⁺CD11b⁻ cDCs over fluorescence; blue (MFI = 76.1) represents label control whereas pink (MFI = 716) represents labeled with anti–Qa-1 mAb. Each dot represents one animal. Error bars represent mean ± SEM. Co-IEL, colonic IEL; Co-LP, colonic LP.

Peptide-mediated protection from DSS-induced colitis is lost in Batf3^−/− mice lacking cDC1s

CD103⁺CD11b⁻ cDCs are known to be developmentally controlled by various transcription factors, including Batf3 (41). Batf3 also controls CD8αα⁺ cDCs in the spleen and other lymphoid tissues that, along with CD103⁺ cDCs form the cDC1s, are known for playing a role in intestinal anti-viral CD8⁺ T cell–mediated immunity and tolerance induction (42–45). We first confirmed that Batf3^−/− mice have a substantially reduced number of CD103⁺CD11b⁻ cDCs in the colon (Supplemental Fig. 3A). Additionally, consistent with a compromised CD8⁺ T cell function in Batf3^−/− mice (46), the frequency of TCRαβ⁺CD8αβ⁺ T cells was also reduced in both colonic IEL and LP in these mice (Supplemental Fig. 3B). Importantly, we found that the protection induced by the Qa-1 agonistic peptide against acute colitis (with 2.5% DSS) was lost in Batf3^−/− mice in comparison with WT mice (Fig. 5). Importantly, however, note that the severity of colitis observed in Batf3^−/− mice was apparently lower in comparison with that in the WT mice. To address this potential confounding factor, we induced colitis in Batf3^−/− mice with an increased dose of DSS (3.5%), but again observed that peptide-mediated protection was lost in these mice (Supplemental Fig. 3C). These data suggest that the immune regulation of colitis is dependent on the presence of the Batf3-dependent Qa-1b⁺ cDC1 population in the inflamed epithelial layer of the colon.

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FIGURE 5.

Role of Batf3-dependent cDCs in peptide-mediated protection from colitis

(A) Representative photographs from two independent experiments showing colons from control-treated (−P, upper panel) or peptide-treated (+P, lower panel) Batf3^−/− mice (n = 4–7) from acute DSS colitis model (2.5%). (B) Bar graph showing cumulative colitis scores of control- or peptide-treated Batf3^−/− mice from acute DSS colitis model. (C) Bar graphs showing concentration (pg/ml) values from CBA kit analysis of cytokines (IL-6, TNF-α, IFN-γ, IL-17A, and IL-10) released in supernatant from colon explant culture. Colons were from control or peptide-treated WT B6 mice from acute DSS colitis model. Each dot represents one animal. Error bars represent mean ± SEM.

Peptide-mediated protection results in a selected upregulation of barrier function genes including Muc2 in distal but not in proximal colonic tissue

We wanted to determine whether the CD8⁺ T cell/CD103⁺ DC–mediated immune regulation impacts epithelial functions. We used qRT-PCR analysis to investigate changes in the expression of colon-expressed genes known for barrier protection in peptide-treated mice in comparison with the control group following DSS-induced colitis. We analyzed proximal and distal colon separately since they have displayed differential gene expression (47, 48) and observed that only in the distal, but not proximal, colon peptide administration enhanced the barrier function gene, Muc2 (Fig 6). Notably, Muc2 deficiency causes spontaneous colitis in mice (49). Muc2 has been shown to induce tolerogenic DCs in mice and humans and maintains gut homeostasis and oral tolerance (50). The other important gene found to be upregulated in the distal colon was Krüppel-like factor 4 (Klf4), and there were nonsignificant trends observed in the junctional molecule occludin (Ocln), but there were no trends observed in other molecules investigated, that is, MUC4, ZO1, and CLDN4 (Fig. 6). These data suggest that peptide-mediated activation of TCRαβ⁺CD8αα⁺ T cells in colon enhances expression of genes whose products play a key role in the gut barrier function.

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FIGURE 6.

Administration of a Qa-1b agonist peptide increases expression of certain genes in distal colon known for barrier function enhancement

Scattered plots showing relative mRNA expression (over housekeeping gene, L32) in proximal and distal colon from control- or peptide-treated animals in the acute DSS colitis model in WT B6 mice (n = 5–9). Each dot represents one animal. Data are representative of two independent experiments. Error bars represent mean ± SEM. A Student’s t test was used to determine statistical significance. *p < 0.05, **p < 0.01.

In the steady state, lack of Qa-1^b is associated with a dramatically altered microbiome and metabolome

The gut microbiome impacts intestinal barrier function and can modulate colonic inflammation (51, 52). Because we observed enhancement of mucin gene expression after administration of the Qa-1^b–agonistic peptide in the colitis model, we examined whether the Qa-1^b pathway has any impact on intestinal microbiota or metabolome that could affect the epithelial barrier even during steady state. We therefore collected fecal samples for 16S rRNA gene amplicon sequencing and untargeted metabolomics analysis from WT and Qa-1b^−/− mice of different ages and sex housed in our animal facility and at two different time points separated by 6 mo. We adopted this randomized sampling to avoid potential confounding influences, such as cage-associated effect, on the microbiota other than Qa-1b deficiency. Principal-component analysis (PCA) of the robust Aitchison distances based on the 16S sequencing data revealed that the microbiome profiles of WT and Qa-1b^−/− mice were significantly different (PERMANOVA F = 73.5, p < 0.001) (Fig. 7A). The genera Prevotella and Akkermansia appeared to drive the separation between the genotypes with lesser contributions by the genera Bacteroides and Bacillus along with an undetermined genus from the family Rikenellaceae. Additionally, α diversity, as measured by the Shannon index, was significantly higher in Qa-1b^−/− mice compared with WT (Mann–Whitney U = 3166, p = 3.8e−12, Fig. 7B). Further analysis of microbes that were differentially abundant between the groups were examined via Songbird (53), revealing that Qa-1b^−/− mice had higher proportions of the genera Prevotella, Bacteroides, and Lactobacillus, whereas WT mice were associated with higher proportions of Akkermansia and Bacillus. Differential abundance of Akkermansia was of particular interest because the genus is known to affect mucin production and regulate responses of the gut epithelium in mice and in humans (54–56). To confirm that abundance of A. muciniphila was different between WT and Qa-1b^−/− mice, we measured Akkermansia abundance by qPCR and found that the absolute abundance of Akkermansia in Qa-1b^−/− mice was significantly lower than in WT mice (Mann–Whitney U = 603, p = 4.6e−11) (Fig. 7C).

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FIGURE 7.

Alteration of stool microbiome and metabolome in absence of Qa-1b

(A) Biplot of PCA using robust Aitchison distance of the fecal microbiota using the Earth Microbiome Project protocol 16S V4 amplicon sequencing to assess β diversity between samples and groups. The bacterial composition of Qa-1^−/− mice (gray triangles) is significantly different from WT mice (open circles) (PERMANOVA F = 73.5, p < 0.001). Arrows show the bacterial genera that contribute most to separation on these axes. (B) α Diversity of fecal microbiota measured by Shannon index (Mann–Whitney U = 3166, p = 3.8e−12). (C) Abundance of Akkermansia marker gene copies measured by qPCR (Mann–Whitney U = 564, p = 2.8e−11). (D) Biplot of PCA using robust Aitchison distance of the fecal metabolome based on untargeted liquid chromatography–tandem mass spectrometry. The metabolite composition of Qa-1^−/− mice (gray triangles) is significantly different from WT mice (open circles) (PERMANOVA F = 14.5, p < 0.001). Arrows show identified metabolites that contribute most to separation on these axes. (E) Qa-1^−/− mice had a higher ratio of primary bile acids to primary conjugated bile acids compared with WT mice based on fecal metabolomics (Mann–Whitney U = 178, p = 3.6e−10). Each symbol represents one individual mouse. ****p < 0.0001.

As a measure of the potential functional consequences of the microbial changes, we performed untargeted metabolomics on the same fecal samples used for 16S analysis. Similar to the microbiome, PCA of the β diversity based on robust Aitchison distances revealed that the metabolite profile of Qa-1b^−/− mice was significantly different from WT (PERMANOVA F = 14.5, p < 0.001) (Fig. 7D). Several of the metabolites most associated with Qa-1b^−/− mice are known, as are novel bile acids (57), such as cholic acid and hyocholic acid. Bile acid abundance and composition vary due to both host and microbial contributions (57), and bile acids may be conjugated in the liver, which affects their functions in fat absorption in the intestine. Qa-1^−/− mice had a higher ratio of unconjugated to conjugated primary bile acids compared with WT mice (Mann–Whitney U = 178, p = 3.6e−10) (Fig. 7E) based on Songbird analysis (53).

In steady state, Qa-1b^−/− mice harbor a proinflammatory environment in colon and are accordingly more sensitive to DSS-induced colitis

Next, we investigated whether the colonic tissues in steady state in Qa-1b^−/− mice harbor an enhanced proinflammatory milieu in the steady state. We found enhanced lymphocyte infiltrations into colonic tissue of Qa-1b^−/− in comparison with WT mice (Fig. 8A). Consistently, TCRαβ⁺CD8αβ⁺ adaptive T cells are significantly increased in steady state in the IEL in these mice (Supplemental Fig. 2D). Additionally, in the tissue explant culture, we also observed significantly higher levels of IL-6 in Qa-1b^−/− mice in comparison with WT mice (Fig. 8A). Because CD4 Tregs are important to control inflammation, we also investigated CD4⁺Foxp3⁺ Tregs to probe whether Qa-1b deficiency compromised colonic CD4⁺ Tregs. We did not find a significant reduction in colon IEL and colon LP fractions of CD4⁺Foxp3⁺ Tregs in Qa-1b^−/− mice in comparison with WT mice (Supplemental Fig. 2E).

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FIGURE 8.

Spontaneous proinflammatory milieu of colonic tissue and enhanced sensitivity to DSS-induced colitis in Qa-1b^−/− mice

(A) Representative images showing H&E staining of colon from WT (left panel) and Qa-1b^−/− (right panel) mice (n = 3–5). Arrows indicate accumulation of lymphocytes. Bar graph represents quantification of IL-6 in the supernatant of explant culture from naive mice by ELISA. (B) Comparative body weight loss between Qa-1b^−/− and WT counterparts using 1.5% DSS-mediated acute colitis model. (C) Representative photographs showing colons from WT or Qa-1b^−/− mice from acute DSS colitis model (1.5%). (D) Bar graph showing cumulative colitis scores from 1.5% acute DSS colitis model. Each dot represents one animal. Error bars represent mean ± SEM. (E) Bar graphs showing concentration (pg/ml) values from CBA kit analysis of cytokines (IL-6, TNF-α, IFN-γ, IL-17A, and IL-10) released in supernatant from colon explant culture. Colons were from WT or Qa-1b^−/− B6 mice from acute DSS colitis model (1.5%). Data are representative of two independent experiments. Each dot represents one animal. Error bars represent mean ± SEM. A Student’s t test was used to determine statistical significance. *p < 0.05, **p < 0.01, ***p < 0.001.

We then investigated whether Qa-1b^−/− mice, because of this proinflammatory milieu, respond differentially in the induction of colitis. We chose a dose of DSS that does not precipitate properly into colitis in WT mice in our animal house, i.e., 1.5% DSS instead of the regular 2.5% DSS. When feeding age-matched mice with 1.5% DSS, we observed that whereas the WT mice did not respond with a change in body weight loss, Qa-1b^−/− counterparts suffered significant loss of body weight (Fig. 8B). Accordingly, Qa-1b^−/−mice treated with DSS also developed enhanced gross and histopathological features of colitis (Fig. 8C, 8D). Explant culture of colon tissue demonstrated upward trends in proinflammatory cytokines from Qa-1b^−/− mice treated with low-dose DSS (Fig. 8E). Taken together, our data demonstrate a proinflammatory milieu in colon when the Qa-1b–based regulatory pathway is absent.

IBD patients display a unique pattern of expression of HLA-E, an ortholog for the murine Qa-1^b

Similar to the murine non-classical MHC molecules, humans also express a conserved class Ib MHC molecule, HLA-E, which shares several features with the murine counterpart (58, 59). Therefore, we determined whether HLA-E expression is altered in IBD patients and more specifically in any specific cell subset recently reported in IBD (5). We first compared differential gene expression of two class Ib MHC molecules (HLA-E and CD1d) and one class Ia MHC molecule (HLA-A) between non-inflamed and inflamed colon from descending and ascending colon in refractory Crohn’s disease (CD) using the CERTIFI cohort (GSE100833) (60). Human gene expression data were downloaded from the Gene Expression Omnibus database (60–62). Interestingly, in the descending colon, but not the ascending colon, we observed significantly enhanced gene expression of HLA-E, but not CD1d or HLA-A (Fig. 9A). The enhanced HLA-E gene expression was also supported by increased protein expression from a different colonic CD cohort (63), which included treatment-free samples and samples from patients treated with various medications (Fig. 9B). Human proteomics data were downloaded from the Proteomics Identification Database (63). Next, expression analysis of therapeutic response studies with Infliximab and vedolizumab allowed us to look into the induced restitution phase of the inflammatory disease in patients. In one study, colonic mucosal biopsies were obtained from ulcerative colitis (UC) patients treated with either vedolizumab or infliximab. Samples from before and after therapy along with outcome (response by histological healing to the therapeutic intervention or not) were compared with non-IBD controls (62). In another study, results for before and after the first infliximab treatment in ileal versus colonic CD were compared with those for non-IBD controls (61). In UC colon datasets and in colonic CD, but not in ileal CD, we observed decreased gene expression of HLA-E and not of CD1d and HLA-A (observed in CD) in therapeutic response and also not in non-responders (Fig. 9C, 9D). Next, on a cellular level, taking cue from our murine studies, mapping prominent myeloid cell subsets in UC obtained from a published scRNA-seq dataset (5), we observed overall enhanced expression of HLA genes similar to our observations as in (Fig. 9A. Interestingly, only in cDC1, but not in other myeloid subsets, there was an enhancement of HLA-E expression by both gene average expression level and by abundance (Fig. 9E, Supplemental Table I). Thus, a similarity in the cell-specific expression profile of HLA-E in humans and Qa-1b in mice in anatomically similar inflamed tissues suggests potential involvement of this regulatory axis in IBD.

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FIGURE 9.

Enhanced HLA-E expression in inflamed tissue, with biologic non-response and in selected myeloid cell populations

(A) Box plot showing different class I MHC molecules (HLA-E, CD1D, and HLA-A) expression levels in the groups of inflamed and non-involved regions from ascending colon (n = 48) and descending colon (n = 40) from CD patients (GSE100833). The p value was calculated from two-way ANOVA. (B) Box plot diagram showing the HLA-E protein expression levels in patients with colonic CD. Box plot showing HLA-E protein expression levels in the groups of ulcer edge (n = 8) and non-involved regions (n = 8) (PXD012284). (C) Box plot diagram showing the HLA-E and CD1D expression levels in patients with UC (GSE73661) in the groups of treatment response from vedolizumab (n = 18) and infliximab therapy (n = 23). The p value was calculated from two-way ANOVA. (D) Box plot showing HLA-E, CD1D, and HLA-A expression levels in the groups of infliximab treatment response in ileal (n = 18) and colonic CD (n = 19) (GSE16879). The p value was calculated from two-way ANOVA. (E) Dot plot diagram showing the gene expression levels in myeloid cells from UC patients (n = 18) and healthy individuals (n = 12) (SCP259). Dot size is proportional to prevalence of CD1D⁺/HLA-A⁺/HLA-E⁺ cells in each cell type. Dot color is proportional to gene average abundance in each cell type. Arrowhead indicates trend in increase of expression for HLA-E (in green for cDC1 as opposed to blue for other myeloid cell types).