Dock2 Protects Colitis by Facilitating Akkermansia Colonization via Suppressing IL-22–Reg3 Activity

Min Lu; Shaoting Xu; Ying Tan; Jianping Deng; Bingbing Feng; Ding Qiu; Xinying Wang; Haiyang Sun; Kaile Ji; Bowen Zhu; Shixian Hu; Xueting Wu; Minhu Chen; Yoichiro Iwakura; Xinying Wang; Rui Feng; Yangfan Qi; Ce Tang

doi:10.1007/s10753-026-02511-9

. 2026 Apr 22;49(1):148. doi: 10.1007/s10753-026-02511-9

Dock2 Protects Colitis by Facilitating Akkermansia Colonization via Suppressing IL-22–Reg3 Activity

Min Lu ¹, Shaoting Xu ², Ying Tan ², Jianping Deng ², Bingbing Feng ², Ding Qiu ², Xinying Wang ², Haiyang Sun ², Kaile Ji ², Bowen Zhu ², Shixian Hu ^2,³, Xueting Wu ³, Minhu Chen ³, Yoichiro Iwakura ⁴, Xinying Wang ^1,^✉, Rui Feng ^3,^✉, Yangfan Qi ^5,^✉, Ce Tang ^2,^3,^6,^✉

PMCID: PMC13236751 PMID: 42020880

Abstract

Dedicator of cytokinesis 2 (DOCK2) is a guanine nucleotide exchange factor upregulated in patients with inflammatory bowel disease (IBD), yet its role in intestinal homeostasis remains obscure. Here, we show that both systemic and T cell–specific Dock2-deficient mice develop exacerbated chemical-induced colitis, characterized by reduced CD8⁺ T cells and impaired IFN-γ production, alongside elevated IL-22 and Reg3γ/β antimicrobial peptides (AMPs), and accompanied with decreased colonization of Akkermansia (A.) muciniphila, a beneficial Verrucomicrobia species. Reg3γ/β expression was diminished in IL-22– and RORγt–deficient mice, and both AMPs inhibited A. muciniphila growth. Co-housing with wild-type mice or A. muciniphila reconstitution rescued colitis severity in Dock2-deficient mice. Pharmacologic inhibition of Dock2-Rac1 signaling suppressed IFN-γ in murine and human T cells. Mechanistically, IFN-γ restricted IL-22 by enhancing H3K27 trimethylation on Ahr promoter and suppressing AHR transcription. These findings identify a Dock2–IFN-γ–IL-22–Reg3 axis that controls commensal microbiota and colitis. Targeting Dock2 signaling may offer new therapeutic opportunities in IBD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10753-026-02511-9.

Keywords: Dock2, IBD, Akkermansia, IL-22, Reg3, Gut microbiota, IFN-γ

Introduction

Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic, relapsing inflammatory condition of the gastrointestinal tract that significantly impacts quality of life due to symptoms like diarrhea, abdominal pain, and rectal bleeding [1]. IBD pathogenesis involves complex interactions between genetic susceptibility, gut microbiota, and environmental influences [2]. In a healthy state, intestinal immune homeostasis depends on balanced communication among epithelial cells, commensal microbes, and immune cells. Disruptions in this network—caused by immune regulatory defects, epithelial damage, or external insults—can result in microbial dysbiosis and chronic inflammation [3]. Understanding how host genetics and the microbiota shape mucosal immunity is essential for identifying new therapeutic targets.

Dedicator of cytokinesis 2 (Dock2) belongs to the Dock protein family, which comprises 11 members grouped into four subfamilies (A–D). Dock2 and Dock1 form the Dock-A subfamily. As guanine nucleotide exchange factors (GEFs), Dock proteins activate small GTPases like Rac, which regulate cytoskeletal dynamics [4]. Dock2 contains several functional domains: a DHR1 domain that promotes Rac activation by binding phosphatidylinositol (3,4,5)-trisphosphate (PIP3) [5]; an N-terminal SH3 domain that interacts with ELMO1 to enhance Rac signaling at the plasma membrane [6]; and a phosphatidic acid-binding PBR domain critical for chemotactic signaling [7]. Unlike other Dock proteins, Dock2 is predominantly expressed in lymphocytes and myeloid cells in both mice and humans [4], suggesting a specialized role in immune cell regulation and disease.

Dock2 functions vary among immune cell types. In neutrophils, Dock2 supports chemotaxis, ROS production, and extracellular trap formation [8]. In plasmacytoid dendritic cells (pDCs), it promotes migration [9] and enhances type I interferon secretion via TLR7 and TLR9 signaling [10]. In natural killer (NK) cells, Dock2 facilitates NKG2D receptor signaling and cytotoxic granule release [11]. In lymphocytes, Dock2 modulates TCR signaling, actin remodeling, and T cell proliferation [12], and in B cells, it contributes to development, class switching, and antibody production [13, 14]. Human studies confirm Dock2’s immunological relevance, as DOCK2-deficient patients present with severe immune defects [15, 16].

Although DOCK family members have not been directly linked to IBD, DOCK2 is considered a susceptibility gene for IBD, as a previous study identified a significant association between the SNP variant rs261616 in this gene and IBD (P = 4 × 10⁻⁹), suggesting that DOCK2 dysfunction contributes to the development of IBD [17]. Mice with deficiency of Dock2 are more susceptible to Citrobacter rodentium intestinal infection, implying its role in maintaining gut immune homeostasis [18, 19]. Certain commensals, including Lactobacillus, Clostridium (Firmicutes), and Akkermansia muciniphila (Verrucomicrobia), help regulate mucosal immunity and epithelial integrity [20]. However, whether critical immune factors such as Dock2 affect commensal microbiota and intestinal homeostasis remains obscure.

Cytokines such as IL-22 and IL-17 help maintain epithelial barriers but can also worsen inflammation in IBD [21]. Their expression is regulated by transcription factors like RORγt and AHR [22], yet the upstream immune signals controlling these pathways are not fully defined.

Given this context, we aim to investigate the role of Dock2 in mucosal inflammation and its interaction with the microbiota. Our study explored how Dock2 modulates T cell responses and commensal homeostasis, offering insights into IBD pathogenesis and potential therapeutic avenues.

Results

DOCK2 Deficiency Exacerbates DSS-Induced Colitis, Impairs IFN-γ Production in CD8⁺ T Cells, and Alters IL-22 and Antimicrobial Peptide Expression

Analysis of public bulk RNA-seq data from rectal inflamed tissues of IBD patients (GSE117993) revealed significantly upregulated DOCK2 expression in ulcerative colitis (UC) and Crohn’s disease (CD) patients, including cecal (cCD) and ileal (iCD) subtypes (Fig. 1A). In the GWAS (ebi.ac.uk/gwas) and GeneCards (genecards.org), we found that the SNP variant rs261616 in the DOCK2 gene was significantly associated with IBD, and our own sequencing of gene mutations in 178 IBD patients from Guangdong Province, China, revealed that four patients carried a TT-to-TC mutation at rs7729471, the SNP closest to rs261616, indicating that base mutations in DOCK2 gene also occur in IBD patients from Guangdong (Fig. 1B). To explore DOCK2’s role in intestinal inflammation, we analyzed a single-cell (sc) RNA-seq dataset (GSE193342) of colonic lamina propria (cLP) cells from mice. Dock2 expression was observed in myeloid-derived cells and lymphocytes, including macrophages, dendritic cells, plasma cells, and T cells at steady state (Fig. 1C, S1A). Following DSS challenge, Dock2 expression peaked at day 7 and declined by day 42 during recovery, with the highest level in T cells (Fig. 1C). CD4⁺ and CD8⁺ T cells dominantly expressed Dock2 at steady state (Fig. 1D, S1B).

To determine the physiological relevance of DOCK2, we induced acute colitis in wild-type (WT) and Dock2-deficient (Dock2^–/–) mice with DSS for 7 days, followed by recovery. Dock2^–/– mice exhibited a higher mortality rate, with 80% succumbing by day 12 (Fig. 1E), and more severe weight loss (Fig. 1F). Macroscopic and histological assessments revealed pronounced colonic shortening, cecal inflammation, and epithelial disruption with intense lamina propria infiltration (Fig. 1G-J). Pro-inflammatory cytokines were significantly elevated, while TGF-β was upregulated (Fig. 1K), suggesting a compensatory regulatory response to severe inflammation.

Flow cytometric analysis showed a selective reduction in CD8⁺ T cells but not CD4⁺ or γδT cells in Dock2^–/– cLP (Fig. 1L). Notably, IFN-γ-producing CD8⁺ T cells were reduced, whereas IL-17-producing CD8⁺ and γδT cells were increased (Fig. 1M-1P). Although mRNA expression of transcription factors T-bet (Tbx21) and RORγt (Rorc) were unchanged, IL-22 and its upstream regulator AHR were upregulated (Fig. 1K). Expression analysis of antimicrobial peptides (AMPs) revealed reduced Defensin-4 and elevated lysozymes and Reg3γ&β in Dock2^–/– colons (Fig. 1Q). The frequencies of CD19⁺ B cells, Ly6G⁺CD11b⁺ neutrophils, and Ly6C⁺CD11b⁺ monocytes were unaltered, but NK cells were reduced (Fig. 1L), consistent with observations in DOCK2-deficient patients [16]. Importantly, Dock2 deficiency did not impair tight junction or MHC-II expression (Fig. 1Q), suggesting the exacerbated inflammation was not attributable to epithelial barrier disruption. These results collectively support a protective role for DOCK2 in maintaining mucosal homeostasis during chemically induced, non-infectious colitis.

DOCK2 Deficiency Promotes IL-22 and Reg3 AMP Expression, and Impairs the Colonization of Verrucomicrobia at Steady State

To assess immune alterations under physiological conditions, we profiled Dock2^–/– mice at steady state. No macroscopic signs of inflammation or differences in colon length were observed between WT and Dock2^–/– mice (Fig. 2A, B). However, the frequency of colonic CD8⁺ T cells was significantly reduced (Fig. 2C). Both the proportion and absolute number of IFN-γ–producing CD8⁺ T cells were markedly diminished, whereas IL-17⁺CD8⁺ T cells were increased (Fig. 2D, E). NK cells were also reduced (Fig. 2C), suggesting impaired cytotoxic surveillance in the absence of DOCK2.

Consistently, qPCR analysis confirmed downregulation of IFN-γ and upregulation of IL-22, RORγt (Rorc), and Reg3 AMPs in Dock2^–/– colons (Fig. 2F, G). The mRNA expression of other cytokines, transcription factors, tight junction proteins, and AMPs remained unchanged. Despite the protective role in colitis [23], Muc2 expression was stable under both baseline and inflammatory conditions (Fig. 2H) and MUC2 protein level was also not impaired (Figure S1C), excluding mucin layer defects as a contributor to disease severity. Il18 expression was not impaired (Fig. 2I), arguing against IL-18 deficiency as a cause of reduced IFN-γ production [24].

qPCR profiling of fecal microbiota revealed decreased α-Proteobacteria and Verrucomicrobia and increased Lactobacilli and Deferribacteres in Dock2^–/– mice at steady state (Fig. 2J). Given the anti-inflammatory role of Lactobacilli and the colitogenic potential of Proteobacteria [25, 26], the reduction of Verrucomicrobia may represent a key factor in colitis exacerbation.

Given the upregulation of Rorc and Il22 in Dock2^–/– colons (Fig. 2F), we assessed Rorc^–/– mice to confirm the downregulation of IL-22 and its downstream factors under RORγt-deficient condition. Although proportions of IL-22⁺CD90.2⁺ ILCs and IL-22⁺Lineage⁺ lymphocytes were not altered (Fig. 2K), absolute numbers of IL-17⁺IL-22⁺ cells were reduced in these subsets (Fig. 2L), indicating that RORγt maintains IL-22-producing populations. Correspondingly, Il22 and Reg3g/b AMP mRNA expression were suppressed in Rorc^–/– colons, though Muc2 mRNA expression remained unchanged (Fig. 2M). Strikingly, Rorc^–/– mice under physiological condition exhibited elevated fecal levels of Akkermansia (A.) muciniphila, the dominant species in the Verrucomicrobia phylum (Fig. 2N), inversely mirroring the reduced abundance observed in Dock2^–/– mice (Fig. 2J).

T Cell-Specific DOCK2 Deficiency also Aggravates Colitis in a Commensal Microbiota-Dependent Manner

Although Dock2 is predominantly expressed in T cells, its expression in myeloid and plasma cells (Fig. 1B), complicates the interpretation of its protective function. To dissect its T cell-intrinsic role, we generated T cell-specific Dock2 deficient mice (Cd4-Cre; Dock2^fl/fl). These mice exhibited normal colonic morphology under steady-state conditions, without signs of spontaneous inflammation (Fig. 3A), while showing increased expression of Reg3 AMPs in colon tissues (Fig. 3B).

Fig. 3 — Dock2 signaling in T cells modifies IFN-γ- and IL-22-producing lymphocytes and protects mouse colitis in a commensal microbiota-dependent manner. (A, B) *Dock2*^fl/fl and *Cd4*-cre;*Dock2*^fl/fl mice were sacrificed under physiological conditions (n = 4/group). Gross colonic appearance and colon length measurements (A) were conducted, and the mRNA expression of Reg3 family AMPs in colon tissues (B) were determined by qPCR. (C-M) *Dock2*^fl/fl and *Cd4*-cre;*Dock2*^fl/fl mice were administered 2% DSS in drinking water for 7 days. Body weight loss (C) and disease activity index (D) were monitored daily during colitis induction (n = 3/group). On day 10 post-DSS treatment, mice were sacrificed, and gross colon observations, colon length measurements (E, *Dock2*^fl/fl n = 6, *Cd4*-cre;*Dock2*^fl/fl n = 7), and histological analyses of the distal colon (H&E staining) (F, G, n = 3/group) were conducted. Following leukocyte isolation from the cLP, the proportions of CD4⁺ and CD8⁺ T cells in leukocytes (H, *Dock2*^fl/fl n = 9, *Cd4*-cre;*Dock2*^fl/fl n = 6), IFN-γ⁺ in CD4⁺ and CD8⁺ T cells (I, *Dock2*^fl/fl n = 6, *Cd4*-cre;*Dock2*^fl/fl n = 3) and IL-22⁺ and IL17⁺ populations in CD90.2⁺Lineage^– ILCs (J) and Lineage⁺ lymphocytes (K, *Dock2*^fl/fl n = 6, *Cd4*-cre;*Dock2*^fl/fl n = 5) were quantified using FACS. The mRNA expression levels of genes encoding IL-22, RORγt and AHR in CD90.2⁺Lineage^– sorted ILCs (L, *Dock2*^fl/fl n = 3, *Cd4*-cre;*Dock2*^fl/fl n = 5) and the mRNA expression of *Ifng*, *Il22* and Reg3 family AMPs in colon tissues (M, *Dock2*^fl/fl n = 7, *Cd4*-cre;*Dock2*^fl/fl n = 4) were determined by qPCR. (N-S) *Dock2*^fl/fl and *Cd4*-cre;*Dock2*^fl/fl mice were co-housed for 4 weeks and then administered 2% DSS in drinking water for 7 days. Body weight loss (N) and disease activity index (O) were monitored daily during colitis induction. On day 10 post-DSS treatment, mice were sacrificed, and gross colon observations and colon length measurements (P), and histological analyses of the distal colon (Q, H&E staining) were conducted (n = 3/group). Following leukocyte isolation from the cLP, the proportions of whole CD4⁺ and CD8⁺ T cells in CD45⁺ leukocytes (R) and IFN-γ⁺ in CD4⁺ and CD8⁺ T cells (S) were quantified using FACS (n = 5/group) Data in (A-B) are from one of two, in (C-M) are from one of four, and in (N-S) are from one of two independent experiments. Data in (B-D, F-S) are shown as mean ± SD. Data in (B-D, F-S) were analyzed using unpaired two-tailed Student’s t-test. (ns: not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001)

Following DSS challenge, Cd4-Cre; Dock2^fl/fl mice developed markedly exacerbated colitis compared to Dock2^fl/fl controls. Phenotypes included greater body weight loss (Fig. 3C), diarrhea and rectal bleeding (Fig. 3D), and severe cecal atrophy, colon shortening, and mucosal edema (Fig. 3E, F). Histologically, these mice showed profound inflammatory infiltration and epithelial erosion (Fig. 3G), supporting a T cell-intrinsic role for DOCK2 in mucosal protection. Flow cytometry revealed significant T cell depletion, notably in CD8⁺ subsets (Fig. 3H), and reduced IFN-γ production in both CD4⁺ and CD8⁺ T cells in the colonic lamina propria (Fig. 3I). The proportions of typical macrophage subsets were comparable between Cd4-Cre; Dock2^fl/fl mice and controls (Figure S2A). Similarly, CD11b⁺Ly6C⁺ monocytes and CD11c⁺MHC-II⁺ dendritic cells showed no significant differences. In contrast, CD11b⁺Ly6G⁺ neutrophils were slightly increased in Cd4-Cre; Dock2^fl/fl mice (Figure S2B), likely reflecting the enhanced inflammatory severity in these mice. Notably, IL-22 and IL-17 production was increased exclusively in ILCs, not T cells (Fig. 3J, K), and sorted CD90.2⁺ ILCs showed elevated Il22 and Ahr but not Rorc mRNA expression (Fig. 3L). Colonic tissues from Cd4-Cre; Dock2^fl/fl mice mirrored this with decreased Ifng and increased Il22 and Reg3 AMP mRNA expression (Fig. 3M).

To further evaluate the role of Dock2-mediated T cell responses in colitis, we induced trinitrobenzene sulfonic acid (TNBS)-colitis in Cd4-Cre; Dock2^fl/fl mice, and they also developed more severe colitis, characterized by greater body weight loss (Figure S2C), colon shortening (Figure S2D), and higher histological scores (Figure S2E) than control littermates. Consistent with the DSS model, these mice exhibited marked T cell depletion (Figure S2F) and reduced IFN-γ production, particularly in CD8⁺ T cells (Figure S2G), accompanied by increased IL-22– and IL-17–producing ILCs (Figure S2H). In addition, colonic tissues also showed decreased Ifng and increased Il22, Ahr, and Reg3g/b mRNA expression in Cd4-Cre; Dock2^fl/fl mice (Figure S2I), similar to the expression in Dock2^–/– mice.

To assess the contribution of microbiota, we co-housed Cd4-Cre; Dock2^fl/fl and WT mice for 3 weeks before DSS treatment. Post co-housing, clinical parameters of colitis, including body weight loss (Fig. 3N), stool characteristics (Fig. 3O), cecum and colon morphology (Fig. 3P), and histological inflammation (Fig. 3Q), were equalized. However, IFN-γ–producing CD8⁺ T cells remained reduced in Cd4-Cre; Dock2^fl/fl mice (Fig. 3R, S), indicating that modified microbiota, rather than T cell impairment alone, was essential for colitis exacerbation caused by DOCK2 signaling deficiency.

DOCK2 Deficiency in T Cells also Impairs Akkermansia Intestinal Colonization Which is Essential to Ameliorate the Severe Colitis in Dock2-Deficient Mice

To identify the critical species of commensal bacteria modified and crucial for the colitis phenotype in Dock2-deficient mice, we carried out 16S rRNA sequencing analysis for the fecal microbiota from Cd4-Cre; Dock2^fl/fl and WT mice at steady state. Although species richness was slightly reduced in Cd4-Cre; Dock2^fl/fl compared to WT (Fig. 4A), α-diversity remained similar (Fig. 4B), while β-diversity showed clear separation between groups (Fig. 4C). Cd4-Cre; Dock2^fl/fl mice had reduced Bacteroidota and increased Firmicutes and Campylobacterota (Fig. 4D). Notably, Verrucomicrobia and its major species A. muciniphila were drastically abolished in both Cd4-Cre; Dock2^fl/fl (Fig. 4E, F) and systemic Dock2^–/– mice (Fig. 2J), but enriched in Rorc^–/– mice (Fig. 2N). The LEfSe cladogram shows differentially abundant bacterial taxa between WT and Cd4-cre; Dock2^fl/fl mice: several taxa, including Akkermansiaceae, were significantly enriched in Dock2^fl/fl WT mice, whereas multiple lineages within Bacteroidaceae and related families were expanded in Cd4-cre; Dock2^fl/fl mice (Fig. 4G).

Fig. 4 — DOCK2 deficiency in T cells diminishes intestinal colonization by *Akkermansia*, a commensal crucial for alleviating the severe colitis observed in *Dock2*-deficient mice. (A-G) Fecal DNA from *Dock2*^fl/fl and *Cd4*-cre;*Dock2*^fl/fl mice aged 8–9 weeks under physiological conditions was harvested for bacterial 16S rDNA sequencing. The number of bacterial species in fecal microbiota (A), the α-diversity of the fecal microbiota (B, Simpson/Shannon index), β-diversity of the fecal microbiota (C, PCoA), relative abundance of each bacterial phylum in whole fecal bacteria (D), relative abundance of indicated phyla (E), and relative frequency of each bacterial species with significant change (F) in mouse feces are shown (n = 3/group). Cladogram was also performed by LEfSe analysis (G). Node size corresponds to genus abundance, with larger nodes indicating greater abundance. Node color represents grouping, white nodes in the tree branch indicate a genus with no significant abundance differences between groups; yellow nodes indicate a genus with significantly higher abundance in *Dock2*^fl/fl groups, and green nodes indicate a genus with significantly higher abundance in *CD4*-cre; *Dock2*^fl/fl groups. Each layer of nodes indicates kingdom/phylum/class/order/family/genus/species from the inside-out. (H–K) *Dock2*^fl/fl and *Cd4*-cre;*Dock2*^fl/fl mice were treated with a cocktail of ABX for 1 week, and then were orally colonized with *A. muciniphila* every other day for three times, followed by administration of 1.5% DSS in drinking water for 7 days. Body weight loss (H) and disease activity index (I) were monitored daily during colitis induction. (*Dock2*^fl/fl-non n = 3, *Dock2*^fl/fl-*Akk.* n = 4, *Cd4*-cre;*Dock2*^fl/fl-non n = 3, *Cd4*-cre;*Dock2*^fl/fl-*Akk.* n = 3). On day 10 post-DSS treatment, *A. muciniphila*-colonized indicated mice were sacrificed, and gross colon observations and colon length measurements were conducted (J). Following leukocyte isolation from the cLP, the proportions of CD8⁺ T cells in leukocytes and IFN-γ⁺ in CD8⁺ T cells were quantified using FACS (K) (*Dock2*^fl/fl-Akk. n = 4, *Cd4*-cre; *Dock2*^f^l/fl-Akk. n = 3). Data in (H–K) are from one of two independent experiments. Data in (E, H–K) are shown as mean ± SD. Data in (E, J, K) were analyzed using unpaired two-tailed Student’s t-test, and in (H, I) using one-way ANOVA followed by Tukey’s multiple-comparisons test. (ns: not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001)

To directly test A. muciniphila's protective role, we depleted microbiota with antibiotics and transferred A. muciniphila orally before DSS induction. This intervention alleviated disease symptoms (reducing weight loss, diarrhea, and rectal bleeding) in both genotypes (Fig. 4H, I), and mitigated colonic pathology in Cd4-Cre; Dock2^fl/fl mice (Fig. 4J), despite persistent CD8⁺ T cell and IFN-γ deficiencies (Fig. 4K). These results indicate that loss of DOCK2 in T cells alters gut microbial composition, particularly reducing Akkermansia abundance, which is essential for the suppression of intestinal inflammation.

IL-22-Reg3 AMP Axis Suppresses A. muciniphila Expansion and DOCK2-IFN-γ Axis Inhibits IL-22 Via Impairing Ahr Transcription

To investigate whether IL-22 directly regulates Reg3 AMPs in the colon, we assessed Reg3 expression in Il22^–/– mice at steady state. mRNA expression of Reg3b and Reg3g was significantly reduced compared to WT mice, alongside decreased levels of Tjp1 (encoding tight junction protein ZO1) (Fig. 5A).

Fig. 5 — Reg3 AMPs inhibit *A. muciniphila* expansion, and DOCK2-IFN-γ axis suppresses IL-22 by impairing *Ahr* transcription. (A) WT and *Il22*^–/– mice were sacrificed under physiological conditions, and the mRNA expression levels of genes encoding Reg3γ, Reg3β, and ZO1 in colon tissues were assessed by qPCR (WT, n = 5; *Il22*^–/–, n = 4). (B) *A. muciniphila* was cultured at 37 °C under anaerobic conditions with recombinant Reg3γ or Reg3β (5 μg/ml each peptide) added to the medium. Bacterial growth was measured spectrophotometrically at 3, 6, 9 and 12 h (n = 3 replicates/group). (C) WT mice were intrarectally administered recombinant Reg3γ or Reg3β for 5 h, followed by determination of *A. muciniphila* content in feces via qPCR (n = 4). (D) CD8⁺ or CD4⁺ T cells were isolated from splenocytes of WT mice, and were stimulated with anti-CD3/CD28 antibodies with the addition of DOCK2-Rac1 interaction inhibitor CPYPP. Four days after the stimulation, IFN-γ⁺ in CD8⁺ or CD4⁺ T cells were quantified using FACS (n = 5 replicates/group). (E) CD90.2⁺ ILCs were isolated from splenocytes of WT mice, and were stimulated with IL-1β with the addition of recombinant IFN-γ. Twenty-four hours after the stimulation, the mRNA expression levels of genes encoding IL-22, AhR, and RORγt in ILCs were assessed by qPCR (n = 6 replicates/group). (F) CD90.2⁺ ILCs were isolated from splenocytes of WT mice, and were stimulated with IL-1β with the addition of recombinant IFN-γ, AHR inhibitor BAY218 or AHR agonist ITE. Twenty-four hours after the stimulation, the mRNA expression levels of genes encoding IL-22, AHR, and RORγt in ILCs were assessed by qPCR (n = 3 replicates/group). (G) CD90.2⁺ ILCs were isolated from splenocytes of WT mice, and were stimulated with IL-1β with the addition of recombinant IFN-γ and STAT1 antagonist fludarabine. Twenty-four hours after the stimulation, the mRNA expression levels of genes encoding IL-22, AHR, and RORγt in ILCs were assessed by qPCR (n = 3 replicates/group). (H) Logo plot of the predicted binding motif of the transcription factor STAT1 to the *AhR* promoter. (I) The efficiency of STAT1 overexpression was confirmed by immunoblot analysis. (J) AHR mRNA levels in HT29 cells overexpressing STAT1 or empty vector control were quantified by qPCR (n = 3 replicates/group). (K) Schematic of *AHR* promoter regions (P1–P5) with predicted STAT1-binding sites. STAT1 binding was assessed by ChIP using anti-Flag antibody as a bait from paraformaldehyde cross-linked HT29 cells, followed by RT–PCR. (L) *AHR* mRNA levels in HT29 cells treated with IFN-γ (5, 20 or 50 ng/ml) for 48 h were assessed by RT-qPCR (n = 3 replicates/group). (M) Luciferase activity driven by *AHR* promoter was examined in HT29 cells co-transfected with Renilla and pGL3-AHR reporter plasmids, with or without 20 ng/ml IFN-γ (n = 3 replicates/group). (N) H3K27me3 protein levels in HT29 cells treated with LPS or IFN-γ were analyzed by immunoblot. (O) *AHR* mRNA levels in HT29 cells treated with IFN-γ in the presence or absence of GSK126 were quantified by qPCR (n = 3 replicates/group). (P) H3K27me3 protein levels in HT29 cells treated with increasing concentrations of GSK126 were analyzed by immunoblot. (Q) *AHR* mRNA levels in HT29 cells exposed to graded concentrations of GSK126 were assessed by qPCR (n = 3 replicates/group). (R) H3K27me3 enrichment at the *AHR* promoter following IFN-γ treatment for 24 h in HT29 cells were assessed by ChIP coupled with RT–qPCR (n = 3 replicates/group). (S) H3K27me3 enrichment at the *AHR* promoter following IFN-γ treatment with indicated doses in HT29 cells were assessed by ChIP coupled with RT–qPCR (n = 3 replicates/group). (T-V) WT mice were intraperitoneally administered AhR inhibitor BAY-218 (10 mg/kg) every other day for 3 times. On day 6 after the first administration, feces were harvested and *A. muciniphila* content was determined via qPCR (T) (n = 6). The mRNA expression levels of *Ahr* and *Il22* in ILCs (U) (n = 3) and the expression of *Reg3g*, *Reg3b*, *Ahr* and *Il22* in colon tissues (V) (non-treated n = 6, BAY-218 n = 4) were assessed by qPCR. Data in (B) are from one of three and in (A, C-G, I-V) are from one of two independent experiments. Data in (A, B, D-G, J, L, M, O, Q–V) are shown as mean ± SD. Data in (A, J, M, T-V) were analyzed using unpaired two-tailed Student’s t-test, in (C) using paired two-tailed Student’s t-test, and in (B, D-G, L, O, Q-S) using one-way ANOVA followed by Tukey’s multiple-comparisons test. Condition labels shown in the bottom panels apply to all graphs within each column. (ns: not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001)

Given the elevated Reg3β and Reg3γ expression in Dock2^–/– mice and concurrent reduction in A. muciniphila, we hypothesized that Reg3 AMPs exert antimicrobial effects on this commensal. In vitro, recombinant Reg3β and Reg3γ significantly inhibited A. muciniphila growth (Fig. 5B). Consistently, intrarectal administration of Reg3 peptides for 5 h greatly reduced fecal A. muciniphila levels (Fig. 5C).

DOCK2 activates Rac1 to mediate downstream immune signaling [5]. Inhibition of the Dock2-Rac1 interaction using CPYPP in activated splenic T cells resulted in reduced IFN-γ responses in both CD8⁺ and CD4⁺ T cells (Fig. 5D). Since IFN-γ inversely correlates with IL-22–Reg3 expression, we tested its regulatory effect on Il22 transcription. Stimulation of splenic CD90.2⁺ ILCs with IL-1β in the presence of recombinant IFN-γ led to significant suppression of Il22 and Ahr, but not Rorc (Fig. 5E). Further experiments showed that both AHR inhibitor (BAY218) and IFN-γ exposure reduced Il22 and Ahr mRNA expression in ILCs without affecting Rorc (Fig. 5F).

To determine whether STAT1, a key IFN-γ signaling effector [27], is involved in suppressing AHR and IL-22, we used its inhibitor Fludarabine. STAT1 inhibition restored Ahr and Il22 expression suppressed by IFN-γ (Fig. 5G), and in silico prediction using JASPAR identified potential STAT1-binding motifs within the Ahr promoter (Fig. 5H). However, the overexpression of STAT1 in HT29 cells (Fig. 5I) could not suppress AHR transcription (Fig. 5J), and the potential binding site on AHR promoter for STAT1 could not be confirmed by chromatin immunoprecipitation (ChIP) (Fig. 5K).

IFN-γ suppressed AHR mRNA expression in HT29 cells (Fig. 5L) and reduced AHR promoter–driven luciferase activity (Fig. 5M). Because promoter methylation can regulate transcription, we examined histone 3 lysine 27 trimethylation (H3K27me3) in HT29 cells. IFN-γ, but not LPS, increased H3K27me3 levels (Fig. 5N). Treatment with histone methyltransferase EZH2 inhibitor GSK126 abolished IFN-γ–mediated suppression of AHR transcription (Fig. 5O), consistent with its ability to reduce H3K27me3 (Fig. 5P) and restore AHR expression in a dose-dependent manner (Fig. 5Q). These findings indicate that IFN-γ represses AHR transcription by promoting H3K27 trimethylation at AHR promoter. ChIP coupled with RT-qPCR assay revealed the enrichment of H3K27me3 at AHR promoter was significantly enhanced by IFN-γ treatment for 24 h (Fig. 5R) and in a dose-dependent manner (Fig. 5S), further confirming the transcriptional mechanism.

In vivo, AHR inhibition markedly increased A. muciniphila colonization (Fig. 5T), and corresponded with decreased mRNA expression of Ahr and Il22 in ILCs (Fig. 5U) and reduced expression of Ahr, Il22, and Reg3 AMPs in colonic tissues (Fig. 5V). These findings indicate that DOCK2-IFN-γ signaling restricts IL-22 and Reg3 AMP expression via AHR modulation to support A. muciniphila colonization.

DOCK2-IFN-γ Axis is Also Promoted and A. muciniphila Colonization is Decreased in IBD Patients

To assess the relevance of DOCK2 signaling in human intestinal inflammation and microbiota regulation, we analyzed DOCK2 and REG3γ protein expression in colonic tissues from IBD patients. DOCK2 was predominantly detected in lamina propria-infiltrating cells with lymphoid morphology, while REG3γ localized to epithelial cells (Fig. 6A). RNA-seq analysis of ileal and rectal biopsies from CD patients showed significantly elevated DOCK2 and IFNG expression compared to healthy controls (Fig. 6B). Moreover, DOCK2 correlated positively with IFNG, and AHR with IL22, in both anatomical regions (Fig. 6C).

Fig. 6 — DOCK2-IFN-γ axis is also in the development of human IBD. (A) Colon tissues from one CD patient were obtained after resection, and immunohistochemical (IHC) staining for DOCK2 and REG3γ proteins of inflammatory colon tissues was performed. (B) Colon tissues from CD patients and healthy individuals were collected, and the relative mRNA expression of *DOCK2*, *IFNG*, and *REG3G* in ileum and rectum tissues was determined by bulk RNA-seq analysis (HC, n = 44; CD, n = 46). (C) Point plots show the correlation of relative mRNA expression between *DOCK2* and *IFNG*, and between *AHR* and *IL22* by bulk RNA-seq analysis as described in (B). (D) CD3⁺ T cells were isolated from the inflammatory colon tissue after resection, and were stimulated with anti-CD3/CD28 antibodies with the addition of DOCK2-Rac1 interaction inhibitor CPYPP. Four days after the stimulation, the mRNA expression level of *IFNG* was assessed by qPCR (n = 4 replicates/group). (E–G) One public scRNA-seq dataset of colon cells obtained from IBD patients (GSE150516) was reanalyzed. Heatmap shows the expression levels of top typical genes in each identified *DOCK2*⁺ cell cluster (subset) and Umap shows the cell types of *DOCK2*⁺ colonic cells (E). Violin plots display the expression of indicated genes in each identified cell cluster (F). The point plots show the correlation between the expression levels of *DOCK2* and *IFNG*, and between *AHR* and *IL22* in double-positive CD8⁺ or CD4⁺ T cells (G). (H) One public scRNA-seq dataset of colon cells obtained from IBD patients (GSE214695) were reanalyzed, and the point plots show the correlation between the expression levels of *DOCK2* and *IFNG* in double-positive CD8⁺ T cells in pooled colonic cells from 6 UC and 6 CD patients. (I) Point plots show the correlation between the expression levels of *DOCK2* and *CD8A*, *DOCK2* and *IFNG*, *REG3G* and *IL22*, and *AHR* and *IL22* in the colon tissues from all pooled human samples in the public RNA-seq dataset (GSE117993). (J) The relative abundance of *A. muciniphila* in fecal bacteria from IBD patients and healthy individuals was determined by reanalyzing a public metagenomics sequencing dataset (GSE111889, HC n = 429, UC n = 459, CD n = 750). (K) The relative abundance of *A. muciniphila* in fecal bacteria from CD patients and healthy individuals was determined by 16S rDNA sequencing analysis (HC, n = 77; CD, n = 80). (L) The transcriptional level of the *REG3G* gene in colon tissues from non-IBD controls and IBD patients was determined by reanalyzing a public bulk RNA-seq dataset (GSE117993, Not IBD n = 55, IBD n = 135). (M) Point plots show the correlation between the relative abundance of *A. muciniphila* and the expression levels of *REG3G*, *REG3A* or *IFNG* in rectum tissues from the same individual UC patients in the public RNA-seq dataset (GSE111889). Data in (A, D) are from one of two independent experiments. Data in (B, J-L) are shown as mean ± SEM, and in (D) are shown as mean ± SD. Data in (B, D, J-L) were analyzed using unpaired two-tailed Student’s t-test. Correlation significance in panels (C, G-I, M) was determined using Pearson’s correlation coefficient (r²) test. Condition labels shown in the bottom panels apply to all graphs within each column. (ns: not significant, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001)

To functionally evaluate DOCK2-dependent IFN-γ regulation, we isolated cLP CD3ε⁺ T cells from fresh human colonic biopsies and stimulated them with CD3/CD28 antibodies in the presence of DOCK2-Rac1 inhibitor. Inhibition of DOCK2 signaling markedly reduced IFNG expression (Fig. 6D). Consistent with murine data, scRNA-seq reanalysis (GSE150516) identified lymphocytes as the major source of DOCK2 expression in human cLP (Fig. 6E, S3A), with CD8⁺ T cells expressing high levels of IFNG and CD4⁺ T cells expressing IL22 (Fig. 6F, S3B). DOCK2 and IFNG expression were positively correlated in both CD4⁺ and CD8⁺ subsets, while AHR and IL22 correlation was restricted to CD4⁺ T cells (Fig. 6G). Further scRNA-seq analysis (GSE214695) confirmed a positive correlation between DOCK2 and IFNG in CD8⁺ T cells from UC and CD patients (Fig. 6H), and revealed significant associations between DOCK2 and CD8A, AHR and IL22, and REG3G and IL22 in pooled healthy and IBD colon samples (Fig. 6I, GSE117993).

Analysis of gut microbial composition from public datasets revealed a marked decrease in fecal A. muciniphila in IBD patients relative to healthy individuals (Fig. 6J, GSE111889), corroborated by our detection of reduced A. muciniphila in feces from CD patients (Fig. 6K). REG3G expression was elevated in both rectal (Fig. 6B) and colonic tissues (Fig. 6L, GSE117993) of IBD patients. Fecal A. muciniphila abundance was negatively correlated with colonic REG3G and positively associated with IFNG in all non-inflamed human intestinal samples (Fig. 6M, GSE111889), while these correlations could not be observed in inflamed tissue samples (Figure S3C), suggesting the dysbiosis of immune system and gut microbiota under IBD condition. Above all, these results identify a conserved DOCK2–IFN-γ signaling axis in human intestinal tissues, and this axis positively correlates with CD8A and IFNG expression, while inversely linked to A. muciniphila abundance.

Discussion

As a member of the Dock protein family, Dock2 activates Rac1 and regulates cytoskeletal dynamics [5], but unlike other Dock family members, it is predominantly expressed in lymphocytes and myeloid cells, where it regulates immune cell chemotaxis, proliferation, and differentiation [4]. Recent studies have linked Dock2 to immune defense against microbial infections and autoimmune diseases, but its role in mucosal immune homeostasis and IBD remains unexplored. In this study, we examined the potential role of Dock2 and revealed a previously unknown progressive function of Dock2 in promoting IFN-γ production in T cells, in suppressing IL-22-mediated Reg3 family AMP secretion in colonic epithelial cells, and in facilitating A. muciniphila colonization and protecting the host from intestinal inflammation (Figure S3, Graphical Abstract).

The potential role of DOCK2 in pathogen-induced intestinal mucosal damage has been explored in several studies. Dock2^–/– mice exhibit heightened susceptibility to Citrobacter rodentium oral infection, as evidenced by increased mortality, weight loss, elevated bacterial load, and more severe intestinal damage compared to WT mice [18]. During the later stages of the infection, Dock2^–/– mice show significantly higher bacterial burden in the liver, mesenteric lymph nodes, and spleen [18], suggesting systemic dissemination of Citrobacter from the mucosal layer into the bloodstream. This may trigger a systemic cytokine storm, which exacerbates intestinal inflammation. In contrast, the early inflammatory response in Dock2^–/– mice can be partially alleviated by the reinfusion of bone marrow-derived macrophages [19], suggesting that Dock2 regulates macrophage function during the initial stages of bacterial infection-induced mucosal injury. Furthermore, a recent study indicated that both WT and Dock2^–/– mice exhibited similar impaired resistance to Citrobacter-induced intestinal mucosal damage following antibiotic-induced depletion of the intestinal microbiota [28]. This finding implies that the pathogenesis of intestinal inflammation in the absence of Dock2 signaling is not solely driven by immune cell dysfunction but also by dysbiosis of the intestinal microbiota. In the present study, we demonstrated that the deficiency of Dock2 signaling severely impaired the colonic colonization of A. muciniphila, a species belonging to Verrucomicrobia, which plays a central role in protecting the host from colitis. A. muciniphila has emerged as a promising next-generation probiotic [29], linked to improved host health and negatively correlated with various diseases. It is known to interact with its host to modulate immune responses, enhance mucus production, and strengthen the gut barrier function [30–33]. The Dock2-deficiency caused impairment of CD8⁺ T cells or IFN-γ production alone could not influence the colitis without the involvement of microbiota modification, further confirming the indispensability of the commensal mediator in Dock2-directed colitis protection.

Additionally, we identified that the Reg3 family of AMPs, secreted predominantly by intestinal epithelial cells, effectively suppressed the expansion and colonic colonization of A. muciniphila. Reg3 proteins, a subset of C-type lectins, are classified into multiple subtypes (α, β, δ, and γ in mice; α and γ in humans) and are critical in maintaining intestinal homeostasis [34, 35]. Reg3γ exhibits potent bactericidal activity against Gram-positive bacteria by binding to peptidoglycan and forming membrane-penetrating pores [36], while Reg3β targets lipopolysaccharide (LPS) and exerts bactericidal effects against Gram-negative bacteria [37]. Notably, A. muciniphila is a Gram-negative, oval-shaped bacterium [38], with a lipid bilayer and LPS to stimulate Toll-like receptor 4 and NF-κB [39, 40]. Interestingly, A. muciniphila also contains a unique peptidoglycan layer with non-acetylated glucosamine residues, a feature rarely observed in Gram-negative bacteria [41]. These structural characteristics enable A. muciniphila to be recognized and targeted by both Reg3γ and Reg3β, highlighting the role of these antimicrobial peptides in regulating its colonization and function in the gut. One study demonstrated that A. muciniphila improves gut barrier function by restoring the mucus layer thickness and enhancing the intestinal expression of Reg3γ, both of which are altered in metabolic disorders such as obesity [31]. Since A. muciniphila is a frequent inhabitant of the vertebrate mucosal layer [38, 42], this suggests that upregulation of Reg3γ expression may represent a positive feedback mechanism to prevent over-proliferation of A. muciniphila and maintain balanced gut microbiota composition. In the present study, we found the REG3G expression was relatively increased and A. muciniphila was decreased in IBD patients, also suggesting the Reg3γ upregulation-caused impairment of A. muciniphila colonization is one pathogenic factor to exacerbate human colitis.

Reg3 AMPs in the gut also mediate host barrier function as a downstream target of IL-22. Several studies reported that both Reg3β and Reg3γ influence epithelial proliferation, crypt regeneration, and protection of intestinal stem cells and Paneth cells from apoptosis in the tissue damage through the STAT3-IL-22 axis [43, 44]. IL-22 is expressed in a broad array of tissues such as liver, lung, skin, and gastrointestinal tract, and the lymphoid lineage encompassing αβ T cells, γδ T cells, NKT cells and ILCs is the cellular source of IL-22 [45]. There is extensive evidence that IL-22 mediates the protection and regeneration of epithelial tissues in experimental models, including hepatitis, pancreatitis and colitis [46–48]. However, IL-22 can also induce the expression of pro-inflammatory molecules, including IL-1, IL-6, IL-8, IL-11, G-CSF and GM-CSF [48–50], leading to conflicting conclusions as to whether IL-22 is tissue-protective or pro-inflammatory. It is also difficult to judge the actual role of IL-22 in our present study because Dock2^–/– mice exhibited severe colitis with the upregulation of colonic IL-22 and downregulation of A. muciniphila. The IL-22 and Dock2 double deficient mice are needed to clarify the actual involvement of IL-22 in the colitis regulated by Dock2 signaling.

The regulation of IL-22 induction is influenced by multiple factors. Both IL-23 and IL-1β are known to promote the transcription of Il17a and Il22 by activating STAT3, NF-κB, and MAPK signaling pathways, often working synergistically to enhance IL-22 production in ILCs [45]. RORγt and AHR are two transcription factors implicated in IL-22 regulation. AHR supports IL-22 expression by binding dioxin response elements (DREs) within the Il22 promoter or by facilitating the recruitment of RORγt to the promoter [51, 52]. However, the exact role of RORγt in IL-22 induction remains ambiguous. While RORγt directly drives IL-17 transcription in Th17 cells, which can also produce IL-22 [22, 45], our results demonstrated a reduction in the absolute numbers of IL-22⁺IL-17⁺ T cells and ILCs in Dock2-deficient mice. However, the proportion of IL-22⁺ cells within these populations remained unchanged, suggesting that RORγt predominantly regulates Th17 cell populations rather than directly influencing IL-22 production.

We demonstrated that IFN-γ negatively regulates IL-22 and AHR transcription. While direct STAT1-AHR binding was not observed, our data indicate that IFN-γ signaling promotes H3K27 trimethylation to suppress AHR expression. A study in systemic lupus erythematosus implicates type I interferons in repressing AHR and JUN in CD4⁺ T cells [53]. Future work should identify the specific downstream mediators of IFN-γ signaling that drive H3K27me3 deposition at the AHR promoter.

In human intestinal tissues, we observed the presence of a DOCK2-IFN-γ axis. The expression of DOCK2 and IFNG, as well as DOCK2 and CD8A, and AHR and IL22, were positively correlated in samples from IBD patients. Moreover, the abundance of A. muciniphila, the bacterium associated with intestinal health, was significantly reduced in IBD patients, and its abundance was negatively correlated with colonic REG3G and inversely associated with IFNG in non-inflamed rather than in inflamed intestinal tissues. These findings suggest that factors influencing the colonization of A. muciniphila are functional only under steady state conditions. Future studies might be needed to identify additional factors regulating A. muciniphila under IBD condition with the dysbiosis of immune system and gut microbiota.

This study highlights the potential therapeutic value of targeting Dock2 or its downstream pathways in treating mucosal inflammatory diseases. By elucidating the interaction between Dock2, immune regulation, and gut microbiota, our findings provide new insights into the pathogenesis of IBD and offer a foundation for developing novel therapeutic strategies.

Materials and Methods

Mice

Systemic Dock2^–/– mice on a C57BL/6J background (Strain# T027257) were obtained from GemPharmatech (Nanjing, China). Rorc^–/– mice on a C57BL/6J background (Cat# S-KO-04113) were obtained from Cyagen Biosciences (Suzhou, China). Il22^–/– mice on a C57BL/6 J background were generated using CRISPR-Cpf1 technology at the experimental animal facilities of the Center for Animal Disease Models, Research Institute for Biomedical Sciences, Tokyo University of Science. Age- and sex-matched C57BL/6J mice, originally sourced from the Guangdong Medical Laboratory Animal Center (Foshan, China), were used for the crossing of Il22^–/– mice and served as the control group in the experiments. Dock2-flox mice (Strain# T017896) were also purchased from GemPharmatech. Cd4-cre mice, generously provided by Dr. Hui Zhang (The First Affiliated Hospital, Sun Yat-sen University), were originally obtained from The Jackson Laboratory (Bar Harbor, ME, USA). Cd4-cre; Dock2^fl/fl mice were generated by crossing Cd4-cre mice with Dock2-flox mice. Dock2-flox littermates were used as the WT control for these conditional knockout mice. All mice were housed under specific pathogen-free conditions with γ-ray-sterilized food and autoclaved bedding in environmentally controlled rooms at the Zhongshan School of Medicine, Sun Yat-sen University. All animal procedures adhered to institutional ethical regulations and were approved by the Experimental Animal Management and Use Committee of Sun Yat-sen University (approval numbers 2020000113, 2021001577). Male mice, aged 8–10 weeks, were used for all in vivo experiments.

Murine DSS-Colitis Model

Acute experimental colitis was induced in 8- to 10-week-old mice by administering 1.5% dextran sulfate sodium (DSS) in drinking water for 7 days, followed by regular drinking water for 3 days. Body weight, stool consistency, and posture were monitored daily to calculate the Disease Activity Index (DAI), which combines scores for weight loss, stool consistency, and body posture. The DAI was scored as follows: weight loss (0: < 5%, 1: 5–10%, 2: 10–15%, 3: > 15%); stool consistency (0: normal, 1: mild loose stools, 2: loose stools, 3: diarrhea and bloody stools); body posture (0: smooth fur without a hunchback, 1: mild fur and a hunchback, 2: moderate fur and a hunchback, 3: severe fur and heavy hunchback). Mice were euthanized at the end of the experiment, and intestinal tissues were collected for further analysis.

Murine TNBS-Colitis Model

Trinitrobenzene sulfonic acid (TNBS)-induced colitis was induced following established protocols, where acute colitis was induced by presensitizing mice with 150 μL of a 1% (w/v) TNBS solution (p2297, Sigma, Darmstadt, Germany) prepared in a 4:1 acetone-to-olive oil mixture and applied to a 1.5 × 1.5 cm shaved dorsal area between the shoulders. On day 8, after the mice were weighed and anesthetized, a 100 μL dose of 2.5% (w/v) TNBS in 50% ethanol was administered intrarectally via a catheter inserted 3–4 cm into the colon, with the mice maintained in a head-down position for 3–5 min. The mice were monitored daily for survival and body weight loss for five days.

Human Samples

The tissue samples of IBD patients or healthy volunteers were obtained from the First Affiliated Hospital, Sun Yat-sen University. Patients were selected based on the primary disease and were treatment-naïve before sample collection. All human samples used in the present study were obtained under the approval of the Committee for Clinical Investigation of the First Affiliated Hospital, Sun Yat-sen University (approval numbers: IIT-2021-654, 2019-55). Informed consent was obtained from each subject for the use of samples. In some experiments, cLP CD3⁺ cells were isolated from colon tissues and were stimulated with Dock2-Rac1 interaction inhibitor (CPYPP: MCE, Cat# HY-110100) for 6 h followed by quantitative reverse transcription PCR (qPCR) or flow cytometry for IFN-γ expression.

Lamina Propria Cell Isolation

Lamina propria (LP) cells were isolated from the colon of euthanized mice. The colon was emptied of contents, opened longitudinally, and cut into 0.2–0.5 cm segments. Intestinal epithelial cells (IECs) were dissociated by shaking the fragments for 30 min at 37 °C in Hank’s Balanced Salt Solution (HBSS) containing 1% FBS and 5 mM EDTA, followed by vortexing for 30 s and centrifugation. The remaining intestine pieces were washed twice with HBSS and subjected to digestion in RPMI-1640 medium containing 200 U/mL Collagenase IV (RuiTaiStar, Cat# C5138-1) and 5 U/mL DNaseI (Sigma-Aldrich) at 37 °C for 2 h. The digested suspension was filtered through a 70-µm cell strainer and centrifuged at 1,500 rpm for 5 min to collect lamina propria cells.

Intestinal ILCs Isolation

LP cells were incubated with surface antibodies, and staining was performed for 30 min at 4 °C with anti-CD11b (1:200), anti-I-A/E (1:200), anti-CD19 (1:200), and anti-CD3 (1:200) antibodies. After washing with HBSS and centrifugation at 1,500 rpm for 5 min, the cells were stained with anti-biotin beads (1:100) for an additional 30 min at 4 °C. Negative selection was performed by magnetic separation. The cells were then incubated for 30 min at 4 °C with anti-CD90.2 (1:200) and washed twice with HBSS. ILCs were sorted as CD90.2⁺ cells and cultured for 18–24 h. In some experiments, IL-1β (30 ng/mL) and IL-23 (40 ng/mL) were added, with or without IFN-γ stimulation. After culture, cells were harvested and analyzed for mRNA expression by qPCR.

Flow Cytometry

For flow cytometry analysis, cells were first washed twice with FACS Hanks buffer (HBSS containing 2% FCS) and treated with 2.4G2 to block non-specific Fc receptor binding. For surface staining, cells were resuspended in FACS buffer (PBS containing 1% BSA and 2 mM EDTA) and incubated with fluorochrome-conjugated antibodies and 7-AAD for 30 min at 4 °C. To assess IL-17A, IFN-γ, or IL-22 production, cells were stimulated with 50 ng/mL phorbol 12-myristate 13-acetate (PMA, Cat# P1585, Merck Millipore, Darmstadt, Germany) and 500 ng/mL ionomycin (Cat# 56,092–82-1, Merck Millipore) or left unstimulated, in the presence of 1 mM monensin (Cat# 475,895, Merck Millipore) for 5 h at 37 °C. After stimulation, cells were washed twice with FACS Hanks buffer. Surface staining was performed with antibodies against cell surface markers for 30 min at 4 °C. Cells were then fixed and permeabilized using Cytofix/Cytoperm solution (Cat# 554,722, BD Biosciences, CA, USA) for 30 min at 4 °C in the dark. After washing with 1 × washing buffer, intracellular staining was performed for 30 min at 4 °C with the appropriate antibodies, followed by two washes with BD wash buffer and resuspension in 500 µL of FACS buffer. All antibodies were used at a dilution of 1:200 or 1:250. Detailed information on the antibodies for FACS is provided in Table S1. Flow cytometry data were acquired on an Attune NxT (Thermo Fisher Scientific) or CytoFLEX (Beckman Coulter, Indianapolis, IN, USA) flow cytometer and analyzed using FlowJo v10.6.2 (BD Biosciences).

16S rDNA Sequencing Analysis

Fecal DNA extraction for 16S rDNA sequencing was carried out using > 500 ng of bacterial genomic DNA. Amplification of the microbial 16S V3-V4 region was achieved using the forward primer (5’-ACTCCTACGGGAGGCAGCA-3’) and the reverse (5’-GGACTACHVGGGTWTCTAAT-3’). Sample-specific 7-bp barcodes were incorporated into the primers for multiplex sequencing. PCR products were purified with Vazyme VAHTSTM DNA Clean Beads (Vazyme, Nanjing, China) and quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA). After the individual quantification step, amplicons were pooled in equal amounts, and pair-end 250 bp sequencing was performed using the Illumina Novaseq platform with Novaseq 6000 SP Reagent Kit (500 cycles) at Shanghai Personal Biotechnology Co., Ltd (Shanghai, China).

Computational Analysis of 16S rRNA Seq Datasets

Microbiome bioinformatics were performed with QIIME2 2019.4 with slight modifications according to the official tutorials (https://docs.qiime2.org/2019.4/tutorials/). Briefly, raw sequence data were demultiplexed using the demux plugin followed by primers cutting with the cutadapt plugin. Sequences were then quality filtered, denoised, merged and chimera removed using the DADA2 plugin. Non-singleton amplicon sequence variants (ASVs) were aligned with mafft and used to construct a phylogeny with fasttree2. Alpha-diversity metrics, observed species, Shannon, Simpson, Faith’s PD, Pielou’s evenness and Good’s coverage, beta diversity metrics, and unweighted UniFrac were estimated using the diversity plugin with samples rarefied to the reasonable number of sequences per sample. Taxonomy was assigned to ASVs using the classify-sklearn naïve Bayes taxonomy classifier in the feature-classifier plugin against the NCBI Database. Linear discriminant analysis Effect Size (LEfSe) was used to determine the bacterial taxa with significant differences in abundance between different groups.

Preprocessing of Single-Cell RNA-Seq Data

Public single-cell RNA sequencing (scRNA-seq) data from DSS-treated C57BL/6 mice (GSE193342) and IBD patients (GSE150516) from the NCBI GEO database were preprocessed and converted into Seurat objects using R version 4.1.3. Cells with unique gene counts > 5000 or < 200, or mitochondrial gene content > 5% were excluded. Gene expression was normalized using the "LogNormalize" method, scaling data by the total expression per cell, multiplying by a factor of 10,000, and log-transforming the result. High-quality cells with > 200 protein-coding genes were retained for downstream analysis.

Identification of Cell Types and Gene Expression by Dimensional Reduction

Following normalization, feature genes exhibiting high cell-to-cell variation were identified. Data were scaled, and linear dimensional reduction was performed. Cells were then clustered based on their expression profiles of feature genes. Cell types were annotated based on the expression of known marker genes: neutrophils (S100a8, Retnlg), fibroblasts (Clec3b, Col1a1), epithelial cells (Epcam), macrophages and dendritic cells (Clec4a1, Trem2), B cells (Cd79a, Ms4a1), T cells (Cd3e, Trbc2), goblet cells (Muc2), NK and NKT cells (Klrb1c, Cd7), γδT cells (Trdv4, Trdc), CD8⁺ T cells (Cd8a), and T regulatory cells (Foxp3).

Fecal Microbiota DNA Isolation and Quantification

Fecal samples were collected from the indicated mice, and total DNA was extracted using the TIANamp Stool DNA Kit (TIANGEN, Cat# DP328). The bacterial and fungal rDNA content was quantified by real-time RT-PCR using 20 ng of fecal DNA and primers as outlined in Table S1. Relative quantities were calculated using the ΔCt method, normalized to total bacterial DNA or fecal weight.

Killing Assay of Antimicrobial Peptides

Akkermansia muciniphila was cultured on Brain Heart Infusion (BHI) medium in the presence of recombinant Reg3β (MCE, Cat# HY-P76003) or Reg3γ (MCE, Cat# HY-P71256) at 5 μg/mL for 3, 6, 9, or 12 h at 37 °C under anaerobic conditions. Bacterial growth was measured by OD600 using a NanoDrop spectrophotometer (Thermo Fisher Scientific). For the in vivo AMP treatment, mice were intra-rectally administered with recombinant Reg3β or Reg3γ for 5 h, and stools were collected before (0 h) and 5 h after the treatment for the following fecal bacterial DNA purification. The modification of Akkermansia content in mouse feces was then assessed using real-time RT-PCR on the QuanStudio5 system and was determined using the ΔCt method and normalized to the expression level of 16S.

Dock2-Rac1 Interaction Inhibition in T Cells

For CD8⁺ T cell isolation, spleens from euthanized mice were homogenized, and erythrocytes were lysed. CD8⁺ T cells were then activated with anti-CD3/CD28 Dynabeads (Thermo Fisher Scientific, Cat# 11456D) for 3–4 days. The Dock2-Rac1 interaction inhibitor CPYPP (MCE, Cat# HY-110100) was added to the culture, and cells were stimulated with PMA for 4–5 h. Cells were then collected, and IFN-γ expression was measured by flow cytometry.

Immunohistochemistry (IHC)

Paraffin-embedded tissue sections were baked at 60 °C for 2 h to remove paraffin, followed by rehydration through xylene and alcohol. Antigen retrieval was performed by microwaving sections in 0.01 M sodium citrate buffer (5 min on high, 25 min on low), followed by cooling to room temperature. Sections were incubated with 3% H₂O₂ for 15 min at 37 °C, washed with PBS, and permeabilized with 0.2% Triton X-100 for 10 min. After blocking with 5% BSA for 30 min at 37 °C, sections were incubated with primary antibodies overnight at 4 °C. After washing, secondary antibodies were applied for 30 min at 37 °C, followed by DAB staining. Sections were observed under a microscope, and the staining intensity was graded as follows: 0 (no staining), 1 + (weak), 2 + (moderate), or 3 + (strong).

Quantitative RT-PCR

RNA was extracted using the Evo M-MLVRT Premix for qPCR kit (AG, Cat# AG11706) and reverse transcribed with an oligo(dT) primer. RT-qPCR was performed with SYBR Green Premix Pro Taq HS qPCR kit (Rox Plus) (AG, Cat# AG11718) on a C1000 Thermal Cycler system (Bio-Rad). Primer sequences are provided in Table S2. mRNA expression was quantified using the Ct method, with Gapdh used as the internal control.

Vectors

A 2.52 kb fragment of the human AHR promoter (− 2480 to + 40 relative to the transcription start site) was amplified by PCR using the following primers: Forward, 5′-CACGGTACCAATCTTGCTTAGTGAAATGAAC-3′; Reverse, 5′-CACGCTAGCTCTCGGAACAGAGCGTC-3′. The purified product was digested with KpnI and NheI and cloned into the pGL3-Basic vector. Constructs were verified by Sanger sequencing.

Luciferase Reporter Assay

HT29 cells were co-transfected with the pGL3-AHR promoter–luciferase construct or pGL3-control, together with a Renilla luciferase plasmid for normalization. After transfection, cells were treated with IFN-γ or solvent control for 48 h. Firefly and Renilla luciferase activities were measured using the Dual-Luciferase® Reporter Assay System (Promega). Relative promoter activity was calculated as the firefly-to-Renilla ratio normalized to solvent-treated controls. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-test.

Immunoblotting Analysis

HT29 cells were maintained in McCoy’s 5 A or RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) at 37 °C with 5% CO₂. Cells were subjected to either ectopic STAT1 expression or GSK126 treatment prior to being harvested. Whole-cell lysates were prepared using RIPA buffer supplemented with 1 mM PMSF and 1 × protease inhibitor cocktail. Protein expression was analyzed by Western blot according to standard protocols. The information of primary anti-STAT1, H3K27me3 and GAPDH antibodies used in this analysis are listed in Supplementary Table 1.

Chromatin Immunoprecipitation (ChIP) Assay

ChIP was performed using the ChIP-IT Express Enzymatic kit (53,008&53,032, Active Motif) according to the manufacturer’s instructions. Briefly, Flag-STAT1–expressing HT29 cells were crosslinked with 1% formaldehyde and quenched with glycine. Chromatin was purified, sonicated to 200–1000 bp fragments, and immunoprecipitated with anti-Flag antibody or control IgG (Santa Cruz). Following reversal of crosslinking, DNA was analyzed by PCR and visualized on 2% agarose gels. Sequences of primers for PCR are provided in Table S2.

Statistical Analysis

Data were analyzed using GraphPad Prism 9 software. Statistical significance was determined using two-tailed unpaired or paired Student’s t-test or two-way ANOVA with Geisser-Greenhouse correction, as appropriate. The difference in gut microbiota composition between groups was assessed by an unpaired t-test. The log-rank test was applied for comparing survival curves. Disease activity index and histological score were analyzed using the Mann–Whitney U test. The Spearman's correlation test employed to analyze the correlation was performed using the R software (version 4.1.3). P-values < 0.05 were considered statistically significant (*p < 0.05; **p < 0.01; ***p < 0.001). Further details on the specific tests used can be found in the respective figure legends.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 7472 KB)^{(7.3MB, pdf)}

Acknowledgements

This work was supported by the Guangdong Basic and Applied Basic Research Foundation (2021A1515110208, M.L.), General Program of the National Natural Science Foundation of China (82070564, C.T.), the Foundation of the 100 Talents Program of Sun Yat-Sen University (Y61231, C.T.), the Fundamental Research Funds for the Central Universities, Sun Yat-sen University (C.T.), the General Program of the National Natural Science Foundation of China (82370540, C.T.) and General Program of the Natural Science Foundation of Guangdong Province, China (2024A1515013236, C.T.).

Authors’ Contributions

M.L., S.X., and Y.T. contributed significantly to the work and wrote the manuscript in collaboration with J.D., B.F., D.Q., X.W., H.S., K.J. and B.Z. Under the supervision of M.C., X.W. and R.F. collected stools and colon tissues from CD patients and healthy people, and analyzed gene transcript and 16 s rDNA sequencing. S.X. performed 16S ribosomal and single-cell RNA sequencing analysis. S.H. performed the SNP analysis of IBD patients. Y.Q. performed the ChIP and luciferase assay and methylation analysis. C.T. generated IL-22-deficient mice for this study, with Y.I. providing advice for mutant mouse generation. C.T. organized and supervised the whole project and edited the manuscript in collaboration with Y.Q., X.W., and R.F.

Data Availability

Raw sequencing files for bacterial 16S DNA sequence analysis have been deposited in Gene Expression Omnibus of NCBI (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi), and can be accessed with GEO accession GSE288392 and secure token klkfmecktxszlwz. Data supporting the findings of this study are all available in this article, and source data are provided in Supplementary Information files.

Declarations

Ethics Approval

All animal procedures adhered to institutional ethical regulations and were approved by the Experimental Animal Management and Use Committee of Sun Yat-sen University (approval numbers 2020000113, 2021001577) and complied with the NIH Guide for the Care and Use of Laboratory Animals. All human samples used in the present study were obtained under the approval of the Committee for Clinical Investigation of the First Affiliated Hospital, Sun Yat-sen University (approval numbers: IIT-2021–654, 2019–55) and conformed to the principles of the Declaration of Helsinki. Informed consent was obtained from each subject for the use of samples.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Min Lu, Shaoting Xu and Ying Tan these authors contributed equally.

Contributor Information

Xinying Wang, Email: sunwingwxy@163.com.

Rui Feng, Email: fengr7@mail.sysu.edu.cn.

Yangfan Qi, Email: yfqi@suda.edu.cn.

Ce Tang, Email: tangc7@mail.sysu.edu.cn.

References

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Associated Data

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

Supplementary Materials

Supplementary file1 (PDF 7472 KB)^{(7.3MB, pdf)}

Data Availability Statement

[CR1] 1.Xavier, R.J., and D.K. Podolsky. 2007. Unravelling the pathogenesis of inflammatory bowel disease. Nature 448 (7152): 427–434. [DOI] [PubMed] [Google Scholar]

[CR2] 2.Graham, D.B., and R.J. Xavier. 2020. Pathway paradigms revealed from the genetics of inflammatory bowel disease. Nature 578 (7796): 527–539. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR3] 3.Caruso, R., B.C. Lo, and G. Nunez. 2020. Host-microbiota interactions in inflammatory bowel disease. Nature Reviews. Immunology 20 (7): 411–426. [DOI] [PubMed] [Google Scholar]

[CR4] 4.Ji, L., S. Xu, H. Luo, and F. Zeng. 2022. Insights from DOCK2 in cell function and pathophysiology. Frontiers in Molecular Biosciences 9 : 997659. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR5] 5.Miyamoto, Y., and J. Yamauchi. 2010. Cellular signaling of Dock family proteins in neural function. Cellular Signalling 22 (2): 175–182. [DOI] [PubMed] [Google Scholar]

[CR6] 6.Stevenson, C., G. de la Rosa, C.S. Anderson, P.S. Murphy, T. Capece, M. Kim, and M.R. Elliott. 2014. Essential role of Elmo1 in Dock2-dependent lymphocyte migration. The Journal of Immunology 192 (12): 6062–6070. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Nishikimi, A., H. Fukuhara, W. Su, T. Hongu, S. Takasuga, H. Mihara, Q. Cao, F. Sanematsu, M. Kanai, H. Hasegawa, Y. Tanaka, M. Shibasaki, Y. Kanaho, T. Sasaki, M. A. Frohman, and Y. Fukui. 2009. Sequential regulation of DOCK2 dynamics by two phospholipids during neutrophil chemotaxis. Science 324 (5925): 384–387. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Kunisaki, Y., A. Nishikimi, Y. Tanaka, R. Takii, M. Noda, A. Inayoshi, K. Watanabe, F. Sanematsu, T. Sasazuki, T. Sasaki, and Y. Fukui. 2006. DOCK2 is a Rac activator that regulates motility and polarity during neutrophil chemotaxis. The Journal of Cell Biology 174 (5): 647–652. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Gotoh, K., Y. Tanaka, A. Nishikimi, A. Inayoshi, M. Enjoji, R. Takayanagi, T. Sasazuki, and Y. Fukui. 2008. Differential requirement for DOCK2 in migration of plasmacytoid dendritic cells versus myeloid dendritic cells. Blood 111 (6): 2973–2976. [DOI] [PubMed] [Google Scholar]

[CR10] 10.Gotoh, K., Y. Tanaka, A. Nishikimi, R. Nakamura, H. Yamada, N. Maeda, T. Ishikawa, K. Hoshino, T. Uruno, Q. Cao, S. Higashi, Y. Kawaguchi, M. Enjoji, R. Takayanagi, T. Kaisho, Y. Yoshikai, and Y. Fukui. 2010. Selective control of type I IFN induction by the Rac activator DOCK2 during TLR-mediated plasmacytoid dendritic cell activation. The Journal of Experimental Medicine 207 (4): 721–730. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Sakai, Y., Y. Tanaka, T. Yanagihara, M. Watanabe, X. Duan, M. Terasawa, A. Nishikimi, F. Sanematsu, and Y. Fukui. 2013. The Rac activator DOCK2 regulates natural killer cell-mediated cytotoxicity in mice through the lytic synapse formation. Blood 122 (3): 386–393. [DOI] [PubMed] [Google Scholar]

[CR12] 12.Sanui, T., A. Inayoshi, M. Noda, E. Iwata, M. Oike, T. Sasazuki, and Y. Fukui. 2003. DOCK2 is essential for antigen-induced translocation of TCR and lipid rafts, but not PKC-theta and LFA-1, in T cells. Immunity 19 (1): 119–129. [DOI] [PubMed] [Google Scholar]

[CR13] 13.Wang, J., L. Xu, S. Shaheen, S. Liu, W. Zheng, X. Sun, Z. Li, and W. Liu. 2017. Growth of B cell receptor microclusters is regulated by PIP(2) and PIP(3) equilibrium and Dock2 recruitment and activation. Cell Reports 21 (9): 2541–2557. [DOI] [PubMed] [Google Scholar]

[CR14] 14.Ushijima, M., T. Uruno, A. Nishikimi, F. Sanematsu, Y. Kamikaseda, K. Kunimura, D. Sakata, T. Okada, and Y. Fukui. 2018. The Rac activator DOCK2 mediates plasma cell differentiation and IgG antibody production. Frontiers in Immunology 9 : 243. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Dobbs, K., C. Dominguez Conde, S. Y. Zhang, S. Parolini, M. Audry, J. Chou, E. Haapaniemi, S. Keles, I. Bilic, S. Okada, M. J. Massaad, S. Rounioja, A. M. Alwahadneh, N. K. Serwas, K. Capuder, E. Ciftci, K. Felgentreff, T. K. Ohsumi, V. Pedergnana, B. Boisson, S. Haskologlu, A. Ensari, M. Schuster, A. Moretta, Y. Itan, O. Patrizi, F. Rozenberg, P. Lebon, J. Saarela, M. Knip, S. Petrovski, D. B. Goldstein, R. E. Parrott, B. Savas, A. Schambach, G. Tabellini, C. Bock, T. A. Chatila, A. M. Comeau, R. S. Geha, L. Abel, R. H. Buckley, A. Ikinciogullari, W. Al-Herz, M. Helminen, F. Dogu, J. L. Casanova, K. Boztug, and L. D. Notarangelo. 2015. Inherited DOCK2 deficiency in patients with early-onset invasive infections. The New England Journal of Medicine 372 (25): 2409–2422. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Alizadeh, Z., M. Mazinani, L. Shakerian, M. Nabavi, and M.R. Fazlollahi. 2018. DOCK2 deficiency in a patient with hyper IgM phenotype. Journal of Clinical Immunology 38 (1): 10–12. [DOI] [PubMed] [Google Scholar]

[CR17] 17.Wang, B.R., J. Wang, T. Tian, S.X. Zhang, Y.Q. Zhao, S.Y. Meng, Z.Y. Wu, F. Huang, J. Zeng, and J. Ni. 2024. Genetic correlation, shared loci, but no causality between bipolar disorder and inflammatory bowel disease: A genome-wide pleiotropic analysis. Journal of Affective Disorders 348: 167–174. [DOI] [PubMed] [Google Scholar]

[CR18] 18.Liu, Z., S.M. Man, Q. Zhu, P. Vogel, S. Frase, Y. Fukui, and T.D. Kanneganti. 2016. DOCK2 confers immunity and intestinal colonization resistance to Citrobacter rodentium infection. Scientific Reports 6: 27814. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Ji, L., Y. Chen, L. Xie, and Z. Liu. 2021. The role of Dock2 on macrophage migration and functions during Citrobacter rodentium infection. Clinical and Experimental Immunology 204 (3): 361–372. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Skelly, A.N., Y. Sato, S. Kearney, and K. Honda. 2019. Mining the microbiota for microbial and metabolite-based immunotherapies. Nature Reviews Immunology 19 (5): 305–323. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Dock2 Protects Colitis by Facilitating Akkermansia Colonization via Suppressing IL-22–Reg3 Activity

Min Lu

Shaoting Xu

Ying Tan

Jianping Deng

Bingbing Feng

Ding Qiu

Xinying Wang

Haiyang Sun

Kaile Ji

Bowen Zhu

Shixian Hu

Xueting Wu

Minhu Chen

Yoichiro Iwakura

Xinying Wang

Rui Feng

Yangfan Qi

Ce Tang

Abstract

Supplementary Information

Introduction

Results

DOCK2 Deficiency Exacerbates DSS-Induced Colitis, Impairs IFN-γ Production in CD8+ T Cells, and Alters IL-22 and Antimicrobial Peptide Expression

Fig. 1.

DOCK2 Deficiency Promotes IL-22 and Reg3 AMP Expression, and Impairs the Colonization of Verrucomicrobia at Steady State

Fig. 2.

T Cell-Specific DOCK2 Deficiency also Aggravates Colitis in a Commensal Microbiota-Dependent Manner

Fig. 3.

DOCK2 Deficiency in T Cells also Impairs Akkermansia Intestinal Colonization Which is Essential to Ameliorate the Severe Colitis in Dock2-Deficient Mice

Fig. 4.

IL-22-Reg3 AMP Axis Suppresses A. muciniphila Expansion and DOCK2-IFN-γ Axis Inhibits IL-22 Via Impairing Ahr Transcription

Fig. 5.

DOCK2-IFN-γ Axis is Also Promoted and A. muciniphila Colonization is Decreased in IBD Patients

Fig. 6.

Discussion

Materials and Methods

Mice

Murine DSS-Colitis Model

Murine TNBS-Colitis Model

Human Samples

Lamina Propria Cell Isolation

Intestinal ILCs Isolation

Flow Cytometry

16S rDNA Sequencing Analysis

Computational Analysis of 16S rRNA Seq Datasets

Preprocessing of Single-Cell RNA-Seq Data

Identification of Cell Types and Gene Expression by Dimensional Reduction

Fecal Microbiota DNA Isolation and Quantification

Killing Assay of Antimicrobial Peptides

Dock2-Rac1 Interaction Inhibition in T Cells

Immunohistochemistry (IHC)

Quantitative RT-PCR

Vectors

Luciferase Reporter Assay

Immunoblotting Analysis

Chromatin Immunoprecipitation (ChIP) Assay

Statistical Analysis

Supplementary Information

Acknowledgements

Authors’ Contributions

Data Availability

Declarations

Ethics Approval

Competing interests

Footnotes

Contributor Information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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DOCK2 Deficiency Exacerbates DSS-Induced Colitis, Impairs IFN-γ Production in CD8⁺ T Cells, and Alters IL-22 and Antimicrobial Peptide Expression