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Research ArticleGastroenterologyOncology Free access | 10.1172/JCI98554 Graft-versus-host disease propagation depends on increased intestinal epithelial tight junction permeability Sam C. Nalle,1 Li Zuo,2,3 Ma. Lora Drizella M. Ong,2 Gurminder Singh,1,2 Alicia M. Worthylake,2 Wangsun Choi,2 Mario Cabrero Manresa,2 Anna P. Southworth,2 Karen L. Edelblum,1,4 Gregory J. Baker,5 Nora E. Joseph,1 Peter A. Savage,1 and Jerrold R. Turner1,2 First published January 22, 2019 - More info Abstract Graft-versus-host disease (GVHD) is a complication of hematopoietic stem cell transplantation (HSCT) that affects multiple organs. GVHD-associated intestinal damage can be separated into two distinct phases, initiation and propagation, which correspond to conditioning-induced damage and effector T cell activation and infiltration, respectively. Substantial evidence indicates that intestinal damage induced by pretransplant conditioning is a key driver of GVHD initiation. Here, we aimed to determine the impact of dysregulated intestinal permeability on the subsequent GVHD propagation phase. The initiation phase of GVHD was unchanged in mice lacking long MLCK (MLCK210), an established regulator of epithelial tight junction permeability. However, MLCK210-deficient mice were protected from sustained barrier loss and exhibited limited GVHD propagation, as indicated by reduced histopathology, fewer CD8+ effector T cells in the gut, and improved overall survival. Consistent with these findings, intestinal epithelial MLCK210 expression and enzymatic activity were similarly increased in human and mouse GVHD biopsies. Intestinal epithelial barrier loss mediated by MLCK210 is therefore a key driver of the GVHD propagation. These data suggest that inhibition of MLCK210-dependent barrier regulation may be an effective approach to limiting GVHD progression. Graphical Abstract Introduction Allogeneic hematopoietic stem cell transplantation (HSCT) is used in the treatment of neoplastic and immune disorders. Graft-versus-host disease (GVHD), in which donor-derived T cells target recipient alloantigens to cause tissue pathology, is a common, and frequently severe, complication of HSCT (1). Tissue damage that occurs as a result of pretransplant conditioning is an important factor in GVHD initiation (2, 3), and we have demonstrated that this primarily reflects a requirement for intestinal injury and associated barrier loss (4). Thus, although conditioning-induced damage typically resolves before GVHD is clinically apparent, the two processes are closely linked. Although efforts to reduce conditioning-associated intestinal damage for prevention of GVHD initiation have shown some efficacy, their utility is limited by the fact that intense antineoplastic therapies and bone marrow ablation are necessary for successful HSCT (2, 3). We therefore focused on the less-well-defined mechanisms by which barrier loss promotes ongoing attack of recipient tissues, i.e., GVHD propagation, which is associated with local T cell recruitment and apoptosis of intestinal crypt epithelial cells (5, 6). Identification of these mechanisms and means to prevent GVHD propagation could have tremendous therapeutic potential (7–9). Sustained intestinal barrier loss has been proposed as a contributor to GVHD propagation based on the observation that the degree of intestinal barrier loss correlates with disease severity in patients and mice with GVHD (4, 6, 8–13). However, it remains unclear whether this increased permeability is a consequence of disease or a primary driver of disease propagation. This difficulty in separating cause from effect has prevented detailed characterization of intestinal barrier dysfunction as a contributor to GVHD pathogenesis. To resolve this, we focused on defining mechanisms and consequences of intestinal barrier loss during GVHD propagation. Here, our analysis of human GVHD biopsies revealed elevated expression and enzymatic activity of long myosin light chain kinase (MLCK210), a well-defined regulator of tight junction permeability (2, 14–16), suggesting that MLCK210-dependent alterations in barrier function may drive GVHD propagation. Consistent with this hypothesis, mechanistic studies in mice revealed that MLCK210 deficiency in recipient mice reduced GVHD propagation. Our studies demonstrate a requirement for MLCK210-dependent intestinal permeability increases during the propagation phase and indicate that intestinal epithelial MLCK210 may be an accessible target for limiting GVHD incidence and severity. Results MLCK210 expression and activity are increased in human GVHD. In an effort to understand GVHD propagation, we analyzed intestinal biopsies from patients with GVHD for common hallmarks of intestinal damage and altered intestinal permeability. Although patients with GVHD have increased intestinal permeability (17), epithelial damage is limited to scattered apoptotic crypt epithelial cells in most cases (Figure 1A) (18–20). Our analyses therefore focused on patients with epithelial apoptosis but without greater degrees of epithelial damage. Tight junction and epithelial structure within intestinal biopsies from these GVHD patients were generally intact, as indicated by unaltered distribution of the tight junction protein zonula occludens–1 (ZO-1) and actin relative to healthy control subjects (Figure 1B). We therefore asked whether expression of MLCK210, a principal regulator of the tight junction leak pathway, was increased in small intestinal biopsies from patients with GVHD relative to healthy controls (Figure 1C). GVHD biopsies exhibited increased MLCK210 expression, and enhanced enzymatic activity, as indicated by increased myosin II regulatory light chain (MLC) phosphorylation (Figure 1D). These data are consistent with the hypothesis that MLCK210-mediated changes in tight junction permeability are associated with GVHD pathogenesis in human subjects. Figure 1 MLCK210 expression and myosin light chain phosphorylation are increased within the intestinal epithelium of patients with GVHD. (A) Representative histopathology of human small intestinal biopsies. Arrowhead denotes an apoptotic cell. Scale bars: 50 μm (top), 10 μm (bottom). (B) Human small intestinal biopsies from healthy controls (left) or GVHD patients (right) were immunostained for ZO-1 (red), β-actin (white), and Hoechst 33342 (blue). Scale bar: 10 μm. Representative images are shown. (C) Biopsies from healthy controls (left) or GVHD patients (right) were immunostained for MLCK210 (brown), counterstained with hematoxylin, and scored from 0 to 3. Each point represents an individual patient. Representative images from n = 9 patients and n = 8 controls are shown. *P < 0.05, Mann-Whitney U test. Scale bar: 10 μm. (D) Biopsies from healthy controls (left) or GVHD patients (right) were immunostained for phosphorylated myosin light chain (pMLC, green) and E-cadherin (ECAD, red). Arrowhead denotes MLC phosphorylation at the perijunctional actomyosin ring. Stains were scored from 0 to 3, with each point representing an individual patient. Representative images from n = 9 patients and n = 8 controls are shown. *P < 0.05, Mann-Whitney U test. Scale bar: 10 μm. Intestinal epithelial MLCK210 expression and activity are increased after allogeneic bone marrow transplantation in mice. We previously developed a minor antigen mismatch GVHD model that recapitulates human GVHD (4). In this bone marrow transplant (BMT) model, transfer of donor bone marrow cells together with mature splenocytes from mice of the 129S6 strain (herein, 129) drives GVHD following infusion into irradiated C57BL/6J (B6) recipient mice. Of note, the 129 and B6 mouse strains are MHC matched (H-2b haplotype), but harbor minor antigen mismatches that trigger allorecognition of recipient B6 cells by donor 129 T cells. This system recapitulates many features of human GVHD after HSCT, which is commonly HLA matched. For example, GVHD propagation is relatively slow in this mouse model, with appearance of clinical features on day 21 (d21) after BMT. This allows unequivocal separation of GVHD propagation from initiation-inducing damage caused by conditioning, as the latter is healed by d14 after irradiation (4). Histological examination on d14 after BMT showed that epithelial damage was limited to rare apoptotic crypt cells after allogeneic BMT (129→B6) but not syngeneic BMT (B6→B6) (Figure 2A). As in human GVHD, jejunal epithelial MLCK expression (Figure 2, B and D) and activity (Figure 2, C and D) were increased after allogeneic BMT. Disease initiation in this model is characterized by IFN-γ, IL-1β, and TNF upregulation within jejunal mucosa after allogeneic, but not syngeneic, BMT (Figure 2E), consistent with previous work showing that TNF and IL-1β signaling induce MLCK210 upregulation (21–23). Thus, this model recapitulates MLCK210 upregulation in human disease and can be utilized to assess the impact of MLCK210-dependent barrier regulation on GVHD pathogenesis. Figure 2 MLCK210 expression and activity as well as cytokines associated with MLCK210 upregulation are elevated in minor mismatch experimental GVHD. B6 WT recipients were lethally irradiated followed by a syngeneic (B6) or allogeneic (129) BMT. Mice were sacrificed 14 days after BMT. (A) Representative histopathology of the small intestine. Arrowheads denote apoptotic epithelial cells. Scale bars: 50 μm (top), 10μm (bottom). (B) Jejunal segments were immunostained for MLCK210 (green) and E-cadherin (red). Arrowheads indicate the location of the perijunctional actomyosin ring. Images are representative of >3 independent experiments. Quantitative analysis is shown in D. Scale bar: 10 μm. (C) Jejunal segments were immunostained for phosphorylated myosin light chain (pMLC, green) and E-cadherin (red). Arrowheads indicate the location of the perijunctional actomyosin ring. Images are representative of >3 independent experiments. Quantitative analysis is shown in D. Scale bars: 50 μm (top), 10 μm (bottom). (D) MLCK210 expression and MLC phosphorylation were determined morphometrically. Each point represents an average of 4 fields from one segment of tissue from a single mouse. Two segments were analyzed per mouse. Data are normalized to the mean of mice that did not receive BMT. MLCK210 mRNA was determined by quantitative PCR (qPCR) in purified epithelial cells. Each point represents an individual mouse. Data are normalized to the mean of mice that did not receive BMT. *P < 0.05, 2-tailed t test (B6→WT vs. 129→WT). (E) Jejunal cytokines were determined by ELISA. Each point represents an individual mouse. *P < 0.05, 2-tailed t test (B6→WT vs. 129→WT). Experimental GVHD-associated barrier loss requires intestinal epithelial MLCK210. Epithelial MLCK210 regulates tight junction permeability in two distinct ways. Modest MLCK210 activation, such as that induced by physiological stimuli, increases paracellular permeability to molecules with diameters up to ~8 Å (24, 25). In contrast, activation of MLCK210 by pathologic stimuli, such as TNF, increases tight junction permeability to larger molecules, including those with diameters of 28 Å and 70 Å (2, 14, 26–28). To assess these distinct modes of MLCK210-dependent barrier loss, we measured intestinal permeability of fluorescein and 4-kDa dextran (Figure 3A), which have diameters of 8 Å and 28 Å, respectively, in WT and MLCK210-deficient (MLCK–/–) mice on the B6 background that received a BMT from WT 129 donors. The MLCK–/– mice lack MLCK210 but display normal expression of the shorter, smooth muscle MLCK protein that is derived from the same Mylk gene (2, 29). Figure 3 Allogeneic BMT fails to induce barrier dysfunction in MLCK–/– mice. (A) Probes used to measure MLCK210-dependent barrier loss. (B) Intestinal permeability to fluorescein was evaluated on d14 after syngeneic (B6→WT) or allogeneic (129→WT or MLCK–/–) BMT. Values are normalized to the mean of WT mice that did not receive BMT. Each point represents an individual mouse. *P < 0.05, 2-tailed t test. (C and D) Intestinal permeability to 4-kDa dextran on d14 (C) or d35 (D) after BMT, normalized to the mean of WT mice without BMT. Each point represents an individual mouse. *P < 0.05, 2-tailed t test. (E and F) Jejunum harvested on d35 and immunostained for phosphorylated myosin light chain (pMLC, green) and E-cadherin (ECAD, red). Arrowheads denote perijunctional actomyosin ring. Note the preservation of myosin light chain phosphorylation within villus smooth muscle in MLCK–/– mice. Each point represents the average of 4 fields from one segment of tissue; 2 segments were analyzed per mouse. Data are normalized to the mean of WT mice without BMT. Scale bars: 50 μm (top), 10 μm (bottom). **P < 0.01, ANOVA with Bonferroni’s correction (vs. all other conditions). (G and H) 35 days after BMT, mice were injected with Alexa Fluor 647–BSA and sacrificed 30 minutes later. Confocal imaging demonstrates bright intravascular signal, indicative of retained dye, in WT and MLCK–/– mice without BMT or after syngeneic (B6→B6) BMT. In contrast, intravascular signal is markedly diminished in both WT and MLCK–/– mice after allogeneic (129→B6) BMT. Note the sharp paracellular pattern in MLCK–/– mice, consistent with preservation of the tight junction barrier, relative to the diffuse signal over the epithelium of WT mice (arrowheads). Scale bar: 25 μm. Each point represents an average of 6 regions of lamina propria from one mouse. Data are normalized to mean of WT mice without BMT. **P < 0.01, ANOVA with Bonferroni’s correction (vs. other conditions for each genotype; matched conditions across genotypes were not significantly different). On d14 after BMT, increased intestinal fluorescein permeability was relatively muted in MLCK–/– mice compared with WT controls (Figure 3B). Increased permeability to 4-kDa dextran was not detected on d14, but it was significantly reduced in MLCK–/–, relative to WT, on d35 (Figure 3, C and D). These permeability changes corresponded with increased intestinal epithelial MLC phosphorylation between d14 and d35 after BMT in WT mice (Figure 3, E and F). This was particularly evident within the apical perijunctional actomyosin ring, which interfaces directly with the tight and adherens junctions (30). Increased epithelial MLC phosphorylation was not detected in MLCK–/– mice (Figure 3, E and F). Thus, although several kinases, e.g., Rho and citron kinases, can phosphorylate MLC in other cell types (31), MLCK210 is responsible for increased intestinal epithelial MLC phosphorylation during GVHD progression. Notwithstanding previous studies indicating a role for MLCK210 in endothelial contraction and regulation of microvascular permeability (32, 33), there were no differences between WT and MLCK–/– mice in terms of tissue permeability to intravenously injected albumin 35 days after BMT (Figure 3, G and H). Therefore, the genetic MLCK210 inhibition in this GVHD model limited MLC phosphorylation and paracellular permeability in intestinal epithelia but did not prevent increased microvascular permeability. MLCK210-dependent processes contribute to GVHD progression. Intestinal epithelial tight junction barrier preservation in MLCK–/– mice provides an opportunity to define the contributions of tight junction dysregulation to GVHD progression during the propagation phase. Weight loss (Figure 4A) and disease activity (Figure 4B) were similar in WT and MLCK–/– mice during the first week after minor mismatch BMT, indicating that radiation-induced damage in the initiation phase was not affected by MLCK210 deficiency. Weight loss of MLCK–/– and WT recipients diverged on d28 after allogeneic BMT, and by d35 weight loss in WT mice was 40% greater than that in MLCK–/– mice (Figure 4A). Disease activity of MLCK–/– and WT mice differed within 10 days of BMT, and this discrepancy increased as disease progressed (Figure 4B). Serum TNF levels were also markedly lower in MLCK–/– mice (Figure 4C). Further, long-term survival was improved in MLCK–/–, compared with WT, after allogeneic BMT (Figure 4D). As an additional measure of disease progression, we assessed intestinal mucosal infiltration by CD8+ T cells, the major effectors of tissue damage in GVHD. There were fewer CD8+ T cells within the intestinal mucosa as well as in biliary and skin epithelium of MLCK–/– minor mismatch (129) BMT recipients relative to WT (Figure 4, E and F), in line with the reduced histopathology at these sites in MLCK–/– mice. Further, CD3+ T cell infiltrate density in the small intestine was markedly reduced in MLCK–/–, relative to WT (Figure 4G). Subset analyses failed to show significant differences in numbers of CD4+Foxp3+ regulatory or CD4+T-bet+ Th1-polarized skewed T cells in MLCK–/– versus WT BMT recipients (Figure 4G). Figure 4 GVHD severity is markedly reduced in MLCK–/– mice. B6 WT or MLCK–/– recipients were lethally irradiated, followed by a syngeneic (B6) or allogeneic (129) BMT. (A) Relative weight and (B) disease activity scores (n = 8–12/group). *P < 0.05, 2-tailed t tests on d35 (129→WT vs. 129→MLCK–/–). (C) Serum TNF as determined by ELISA, 35 days after BMT. Each point represents an individual mouse. **P < 0.01, 2-tailed t test (129→WT vs. 129→MLCK–/–). (D) Survival (n = 6–8/group). **P < 0.01, Kaplan-Meier log-rank test (129→WT vs. 129→MLCK–/–). (E and F) Liver, skin, and jejunum were harvested 35 days after BMT and sections immunostained for CD8 (green) and E-cadherin (ECAD, red). (E) Representative images of biliary and squamous (skin) epithelium from WT (left panels) and MLCK–/– (right panels) mice are shown. Arrowheads denote infiltration by CD8+ cells. Scale bars: 20μm. (F) Representative images of jejunum from WT (left) and MLCK–/– (right) mice. Arrowheads denote direct contact of CD8+ cells with the epithelium. Scale bar: 50 μm. (G) Jejunum harvested 35 days after BMT was immunostained for CD3, CD4, Foxp3, and T-bet. Graphs show CD3+, CD4+Foxp3+, or CD4+T-bet+ T cells. Each point represents an individual mouse. **P < 0.01, 2-tailed t test. Cumulatively, these data demonstrate that MLCK210 contributes significantly to systemic GVHD propagation but has no measurable effect on the initiation phase. Although a role for MLCK210 in non-epithelial cell types, e.g., endothelia, cannot be completely ruled out (29, 34), the use of donor cells from WT mice in these studies excludes a role for MLCK210-dependent changes in immune and other bone marrow–derived cells as a potential explanation for reduced disease in MLCK–/– recipients. Intestinal epithelial MLCK210 drives barrier loss and GVHD propagation. To verify that the disease amelioration observed in MLCK–/– BMT recipients was due to deletion of MLCK210 within intestinal epithelia, we asked whether the protection observed in MLCK–/– mice could be reversed by crossing MLCK–/– mice with transgenic mice specifically expressing MLCK within the intestinal epithelium. The MLCKTg mice used express constitutively active MLCK under control of the intestinal epithelium–specific 9-kb villin promoter (35). Weight loss (Figure 5A), disease activity (Figure 5B), survival (Figure 5C), cytolytic CD8+granzyme B+ T cell infiltration (Figure 5D), and histopathology (Figure 5, E and F) of both MLCKTgMLCK–/– and MLCKTg mice were all similar to those of WT mice. In contrast, each of these features of GVHD was significantly ameliorated in MLCK–/– mice relative to WT, MLCKTgMLCK–/–, or MLCKTg mice (Figure 5, A–F). In addition, the hallmark skin ulceration observed in advanced GVHD was similar in MLCKTg and WT mice, while this characteristic was absent and fur texture markedly less perturbed in MLCK–/– mice (Figure 5G). Figure 5 GVHD severity is modulated by intestinal epithelial MLCK210. B6 recipients of the indicated genotypes were lethally irradiated, followed by a 129 BMT. (A) Relative weight and (B) disease activity scores (n = 6–9/group). *P < 0.05, ANOVA with Bonferroni’s correction vs. all other conditions. (C) Survival (n = 8–15/group). *P < 0.05, Kaplan-Meier log-rank test, MLCK–/– compared with all other groups. (D) Sections of jejunum were immunostained for CD8 (green) and granzyme B (red) 35 days after BMT. Representative images are shown. Arrowheads indicate colocalization. Scale bar: 20 μm. Each point represents an individual mouse. **P < 0.01, ANOVA with Bonferroni’s correction for MLCK210-KO mice vs. all other conditions (except syngeneic BMT) on d35. (E) Histopathology of jejunum (arrowheads denote apoptotic epithelial cells), liver (arrowheads denote lymphocytes infiltrating biliary epithelium), and skin (arrowheads denote apoptotic squamous cells, asterisks indicate preserved pilosebaceous units) on d35. Scale bars: intestine, 100 μm, 20 μm; liver, 300 μm, 50 μm; skin, 300 μm. (F) Total pathology scores (sum of jejunum, liver, and skin scores) 35 days after BMT. Each point represents an individual mouse. **P < 0.01, ANOVA with Bonferroni’s correction (vs. all other conditions). (G) Gross photos of 2 mice/group 35 days after BMT. Arrowheads point to hair loss and skin ulcers. Scale bar: 1 cm. (H) Correlation between intestinal permeability to fluorescein at 2 weeks after BMT and GVHD severity 5 weeks after BMT. Each point represents an individual mouse. Colors correspond to those for each condition shown in F. r = 0.75, P < 0.01 by Pearson’s correlation coefficient and degrees of freedom. To better define the impact of MLCK-dependent barrier regulation on GVHD propagation, we assessed overall disease severity on d35 as a function of barrier loss on d14 after BMT. When all 4 genotypes that received allogeneic BMT as well as mice that received syngeneic BMT were considered, there was a strong correlation between ultimate disease severity and permeability increases that occurred much earlier (Figure 5H; r = 0.75, P < 0.01). As a whole, these results indicate that disease propagation and cumulative GVHD severity are driven by MLCK210-dependent regulation of intestinal epithelial permeability. MLCK210 inhibition reduces GVHD in a major antigen mismatch model. In order to test the role of MLCK210 in a separate GVHD model, we injected irradiated B6 recipients (H-2b haplotype) with bone marrow and splenocytes from BALB/c donors (H-2d haplotype). In this pairing the donor and recipient are MHC mismatched, leading to substantial allorecognition of recipient antigen by donor immune cells. This results in a robust graft-versus-host response and rapid GVHD progression. As in minor mismatch GVHD, skin ulcerations (Figure 6A), histopathology (Figure 6, B and C), and disease activity (Figure 6D) were all improved in MLCK–/–, relative to WT, recipients. Despite protection, d35 disease activity scores of MLCK–/– mice receiving major mismatch BMT were substantially greater than those of MLCK–/– mice after minor mismatch BMT. The greater severity of major mismatch GVHD was also apparent in survival of WT mice; ~40% survived to d35 after BALB/c→B6 BMT relative to ~70% after 129→B6 BMT. Nevertheless, survival of MLCK–/– mice on day 35 after major mismatch BMT was more than twice that of WT mice (Figure 6E). Figure 6 GVHD is diminished in MLCK–/– mice following major mismatch BMT. B6 WT or MLCK–/– recipients were lethally irradiated, followed by BALB/c BMT. (A) Gross photos of 3 mice/group 35 days after BMT. Arrowhead points to hair loss and skin ulcers. Scale bar: 0.5 cm. (B) Representative histopathology of jejunum (arrowheads denote apoptotic epithelial cells; arrows indicate intraepithelial lymphocytes), liver (arrowhead indicates intraepithelial lymphocyte; asterisk denotes neutrophils, i.e., active pericholangitis), and skin (asterisk is adjacent to a damaged pilosebaceous gland) on d35. Scale bars: intestine, 200 μm, 20 μm; liver, 200 μm, 20 μm; skin, 100 μm. (C) Total pathology scores (jejunum, liver, and skin) 35 days after BMT. Each point represents an individual mouse. **P < 0.01, 2-tailed t test. (D) Disease activity scores at 35 days after BMT. Each point represents an individual mouse. *P < 0.01, 2-tailed t test. (E) Survival (n = 9 per group). *P < 0.05, Kaplan-Meier log-rank test, MLCK–/– compared with WT. (F) MLCK210 mRNA was analyzed by qPCR in purified jejunal epithelial cells. Each point represents an individual mouse. Data are normalized to the mean of mice that did not receive BMT. **P < 0.01, 2-tailed t test. (G and H) Jejunum was harvested 35 days after BMT and sections immunostained for phosphorylated myosin light chain (pMLC, green) and E-cadherin (ECAD, red). Arrowheads denote perijunctional actomyosin ring. **P < 0.01, 2-tailed t test. Scale bar: 25 μm. (I) Jejunum was harvested 35 days after BMT and immunostained for CD8, granzyme B, and E-cadherin. Left: quantification of CD8+granzyme B+ cells/mm2 of tissue. **P < 0.01, 2-tailed t test. Right: representative images of CD8 (green) infiltration. Arrowheads in low-power views denote intraepithelial CD8+ cells. Scale bars: 50 μm, 10 μm. Similar to minor mismatch disease, major mismatch GVHD was associated with marked increases in intestinal epithelial MLCK210 expression (Figure 6F) and intestinal epithelial MLC phosphorylation in WT mice (Figure 6, G and H). In contrast, no increases in MLC phosphorylation were detected in intestinal epithelia of MLCK–/– mice (Figure 6, G and H). Finally, lamina propria infiltration by CD8+granzyme B+ T cells was significantly greater in WT, relative to MLCK–/–, mice after major mismatch BMT (Figure 6I). Taken together, these results demonstrate that MLCK210 deletion limits propagation of major antigen mismatch GVHD and provides further evidence that intestinal epithelial MLCK210 is a critical regulator of GVHD pathogenesis. MLCK210-dependent intestinal epithelial tight junction barrier loss is associated with polyclonal cytolytic T expansion within mesenteric lymph nodes. While the data above indicate a key role for MLCK210-dependent intestinal paracellular permeability increases in GVHD propagation, they do not explain how intestinal barrier loss is translated to systemic disease. To better assess immune aspects of disease progression, we developed an antigen-specific GVHD model. We used OVA as a model antigen, as the minor antigen(s) responsible for allorecognition have not been defined in the 129→B6 model (36). WT and MLCK–/– B6 mice expressing membrane-bound OVA (mOVATg and mOVATgMLCK–/–) were used as BMT recipients. For these studies, WT B6 bone marrow and splenocytes were supplemented with a minor fraction of splenocytes from congenically disparate (CD90.1) B6 OT-I mice, which express a transgenic T cell receptor reactive to the OVA peptide SIINFEKL in the context of H-2Kb (37). GVHD developed in mOVATg BMT recipients, but not in WT B6 recipients lacking membrane-bound OVA expression, confirming that the OVA peptide serves as a minor mismatch antigen rendering recipient mice susceptible to GVHD (Figure 7, A and B). When mOVATg and mOVATgMLCK–/– BMT recipients were compared, the kinetics with which weight and disease activity scores diverged were similar to that in the 129 B6 allogeneic BMT model. Characteristic histopathological features of GVHD were evident in mOVATg BMT recipients but were significantly decreased in mOVATgMLCK–/– recipients (Figure 7C). Finally, consistent with the results in 129→B6 allogeneic BMT, the density of CD3+ T cells within the small intestine of mOVATg BMT recipients was far greater than that in mOVATgMLCK–/– recipients (Figure 7D). Thus, MLCK210 deletion in this antigen-specific model limits GVHD propagation and recapitulates the effects seen in minor and major antigen mismatch models. Figure 7 Genetic MLCK210 inhibition reduces effector CD8+ T cell accumulation within mesenteric, but not systemic, lymph nodes. B6 mOVATg (n = 14), B6 mOVATgMLCK–/– (n = 11), and B6 WT controls (n = 4) were lethally irradiated, followed by an OT-I BMT consisting of 5 million WT bone marrow cells, 10 million WT splenocytes, and 2 million OT-I splenocytes. (A) Weight and (B) disease activity scores. **P < 0.01, 2-tailed t tests on d35. (C) Pathology scores of GVHD target organs (jejunum, liver, and skin) and representative small intestinal histopathology 35 days after BMT. Each point represents an individual mouse. *P < 0.05, 2-tailed t test. Arrows denote intraepithelial lymphocytes; arrowheads denote apoptotic bodies. Scale bars: 50 μm; inset: 10 μm. (D) Small intestine samples from day 35 after BMT were immunostained for CD3 (green), ZO-1 (red), E-cadherin (ECAD, blue), and Hoechst 33342 (white). Representative images are shown. Scale bar: 50μm. Graph shows CD3+ infiltration in the small intestine 35 days after BMT; each point represents an individual mouse. *P < 0.05, 2-tailed t test. (E) Flow cytometry analysis of cells isolated from spleen, mesenteric lymph nodes (MLN), and axillary/brachial lymph nodes (A/B) on d35 after BMT. The proportions of CD8+ T cells relative to live cells are shown. (F and G) CD8+ T cell intracellular granzyme B expression as evaluated by flow cytometry 35 days after BMT. (F) Representative flow cytometry plots and (G) quantification. Each point represents an individual sample. *P < 0.05, 2-tailed t test. The major advantage of the mOVATg GVHD model is that it allows direct analysis of the CD90.1+ OT-I T cells that drive disease. Based on reduced numbers of tissue-infiltrating T cells in MLCK–/– BMT recipients (Figure 4G and Figure 7D), we expected that the proportion of CD90.1+ T cells within lymph nodes and spleen would be similarly reduced in MLCK–/– recipients. This was not, however, the case. The fractions of CD3+ T cells that were CD90.1+ in spleen, axillary/brachial lymph nodes, and mesenteric lymph nodes of mOVATg and mOVATgMLCK–/– BMT recipients were similar (Figure 7E). This suggested that some other characteristic of the CD90.1+ T cells might explain their enhanced pathogenicity in MLCK210-expressing BMT recipients. Consistent with this, the fraction of CD90.1+CD8+ T cells expressing granzyme B was significantly greater in mesenteric lymph nodes of mOVATg BMT recipients relative to mOVATgMLCK–/– BMT recipients (Figure 7, F and G). Remarkably, this was also the case for polyclonal CD90.1–CD8+ T cells within mesenteric lymph nodes of mOVATg and mOVATgMLCK–/– BMT recipients (Figure 7, F and G). In contrast, the proportions of axillary/brachial lymph nodes and spleen CD90.1+ and CD90.1– CD8+ T cells expressing granzyme B were unaffected by MLCK210 deletion (Figure 7G). These data indicate that MLCK210 expression within the intestinal epithelium specifically enhances the cytolytic potential of CD8+ effector T cells within regional lymph nodes and suggest that this may be a principal mechanism by which increased intestinal epithelial tight junction permeability drives systemic GVHD propagation. Discussion We show here that preventing MLCK-dependent intestinal epithelial tight junction barrier dysfunction can limit GVHD propagation, as defined by reduced tissue damage, cytolytic T cell differentiation, and mortality. The idea that tight junction preservation could be beneficial has long been proposed (4, 13, 38, 39), but the hypothesis has never been tested by selectively preventing disease-associated barrier loss during the propagation phase. Our use of mice lacking MLCK210 allowed us to determine the selective impact of cytoskeletally mediated intestinal epithelial tight junction permeability on GVHD and to distinguish this effect from pretransplant conditioning-associated damage during disease initiation. Our data demonstrate a causal role for MLCK210-dependent tight junction regulation, rather than gross epithelial damage, in driving GVHD propagation after recovery from conditioning-induced damage. The results further suggest that MLCK210-dependent changes in intestinal tight junction permeability promote disease propagation by establishing a local environment that fosters cytolytic effector CD8+ T cell expansion. We also observed reduced CD8+ T cell infiltration in the distant target organs of the liver and skin in MLCK–/– mice after allogeneic BMT compared with WT recipients. We speculate that the decrease in CD8+ T cells in systemic target organs in MLCK–/– mice reflects quelling of the cytokine storm propagated by tight junction–mediated barrier dysfunction. In addition to regulating intestinal epithelial tight junctions, MLCK210 has been reported to regulate endothelial retraction and apoptosis (40–43). Moreover, endothelial damage and increased microvascular permeability have been linked to GVHD pathogenesis (44–46). We therefore considered the alternative hypothesis that the protective effect of MLCK210 deletion could reflect preservation of vascular, rather than intestinal, barrier function. We tested this in two ways. First, we directly assessed vascular permeability to fluorescently tagged albumin. WT and MLCK–/– mice demonstrated similar loss of vascular albumin after BMT. The one qualitative difference was that albumin released from vessels within the villus highlighted sharply defined lateral intercellular spaces with a bright spot just beneath the apical junctional complex in MLCK–/–, but not WT, mice. This suggests that albumin was able to leak out of vessels and across the epithelial basement membrane, but that diffusion was limited by the epithelial tight junction. Although vascular albumin was similarly lost in WT mice, fluorescent albumin within the intestinal epithelium of these mice created wider profiles of lateral intercellular spaces. These data indicate that vascular albumin leakage and barrier loss after BMT are similar but that intestinal epithelial barrier function is preserved during GVHD in MLCK–/–, relative to WT, mice. A potential contribution of endothelial MCLK210 was further probed using a genetic approach. Because tissue-specific MLCK210-knockout mice are not available, we took advantage of MLCKTg mice that express constitutively active MLCK under control of the intestinal epithelium–specific 9-kb villin promoter (14, 15, 47). Expression of this transgene has been shown to restore colitis-associated MLC phosphorylation within intestinal epithelia of MLCK210-deficient mice (15). The transgene also restored GVHD in MLCK–/– mice; the magnitude of disease was similar in WT, MLCKTgMLCK–/–, and MLCKTg mice; and severity in each was greater than that in MLCK–/– mice. Thus, intestinal epithelium–specific MLCK activation and consequent MLC phosphorylation are able to complement MLCK210 deletion. Since the transgene is not expressed in endothelium, the contrast between MLCKTgMLCK–/– and MLCK–/– mice indicates that endothelial MLCK210 is not required for GVHD propagation. This might be surprising, given the ability of MLCK210 to regulate endothelial permeability (29, 48–52). However, our data demonstrate that GVHD-associated increases in microvascular permeability are comparable in WT and MLCK–/– recipients. We must therefore conclude that other effectors (53–57) or direct endothelial damage (40, 44, 46, 58, 59) are responsible for increased microvascular permeability in GVHD. The primary clinical approach to treating GVHD after allogeneic BMT is immunosuppression (7). However, immunosuppression also increases risk of infection; compromises graft viability; and, in the case of HSCT as part of cancer therapy, can dampen graft-versus-tumor activity (60–66). Thus, there is an urgent need for alternate approaches to prevent GVHD development or reduce its severity. The current study identifies MLCK210 as a critical regulator of GVHD propagation and indicates that MLCK210 may be a promising therapeutic target. This will, however, require defining mechanisms to avoid toxicities resulting from inhibition of non-barrier functions of epithelial MLCK210 as well as smooth muscle MLCK, which has an identical catalytic domain (15, 67, 68). These studies clearly distinguish between GVHD initiation and propagation and indicate that MLCK210-dependent increases in intestinal epithelial tight junction permeability are central to propagation. In contrast, previous work from our group and others indicates that tight junction–independent barrier loss, due to epithelial damage, is necessary for GVHD initiation (4). Thus, while barrier loss is critical to both initiation and propagation of GVHD, the mechanisms and impact of barrier loss differ markedly. Finally, these studies demonstrate that the magnitude of increases in intestinal permeability shortly after GVHD initiation, i.e., on d14, correlates with disease severity at later times. Noninvasive analyses of intestinal permeability are relatively easy to accomplish in patients (69, 70). It would therefore be of interest to determine whether intestinal permeability has similar prognostic value in patients. If so, one could envision developing barrier-restorative therapies that are used selectively in patients with increased intestinal permeability at early times after HSCT. In summary, these data show that MLCK210-mediated intestinal epithelial barrier dysfunction is a primary contributor to systemic GVHD propagation. The results also suggest that targeting non-hematopoietic functions, such as epithelial barrier integrity, may provide an alternative to immunosuppression for the treatment of GVHD. Methods Immunohistochemistry and immunofluorescence. Deidentified patient biopsies were obtained from the archives of the University of Chicago Department of Pathology under an IRB-approved protocol. Duodenal biopsies from subjects with GVHD were included only if (i) they were collected 2 or more weeks after HSCT, in order to exclude effects of pretransplant conditioning or other interventions in the peritransplant period; and (ii) clinical and histological features of disease were present. Biopsies from patients who had not undergone HSCT and did not have duodenal disease served as controls. Formalin-fixed mouse tissues were embedded in paraffin and assembled into tissue microarrays before staining. After deparaffinization, 5-μm sections were rehydrated, and antigen was unmasked by boiling in 0.01 citrate (pH 6.0) or 0.01 M Tris/EDTA (pH 9.0), both with 0.05% Tween-20. Slides were stained with rat anti–human ZO-1 (clone 6B6E4), rat anti–mouse ZO-1 (clone R40.76), mouse anti–E-cadherin (Abcam, clone M168), rabbit anti–β-actin (Abcam, ab8227), rabbit anti–phosphorylated MLC (Cell Signaling Technology, catalog 3671), mouse anti-MLCK (MilliporeSigma, clone K36), rat anti-CD3 (Bio-Rad, clone CD3-12), rabbit anti-CD3 (Abcam, clone SP7), biotinylated rat anti-CD8α (Invitrogen, clone 4SM15), biotinylated rat anti-CD4 (Invitrogen, clone 4SM95), rabbit anti-CD4 (Abcam, clone EPR19514), rabbit anti–granzyme B (LifeSpan Biosciences, catalog LS‑B7602), biotinylated rat anti-Foxp3 (Invitrogen, clone FJK-16s), or mouse anti–T-bet (Invitrogen, clone 4B10). MLCK detection in human samples used donkey anti-mouse IgG conjugated to HRP and the Envision+ System-HRP (DAB) kit (Dako). All other primary antibodies were detected using Alexa Fluor–conjugated streptavidin or highly purified secondary Fab′2 fragments (Jackson ImmunoResearch Laboratories Inc.) with Hoechst 33342 (Invitrogen). Stained sections were mounted in Permount for peroxidase stains and ProLong Diamond (Invitrogen) for fluorescent stains. H&E-stained and immunoperoxidase-stained tissues were imaged using a DMLB microscope (Leica) with 10× HC FL PLAN NA0.25 and 40× HC FL PLAN NA0.65 objectives and a MicroPublisher 3.3 CCD camera (QImaging) controlled by QCapture Pro 6. Post-acquisition processing was performed in Adobe Photoshop Lightroom. Fluorescence-stained tissues were imaged using either (i) a DM4000 epifluorescence microscope (Leica) equipped with 63× NA1.32 HCX PlanApo and 20× NA0.70 HC PlanApo objectives and Retiga Exi (QImaging) or Coolsnap HQ2 (Photometrics) cameras or (ii) an Axioplan 2 microscope (Zeiss) with 20× NA0.8 Plan-Apochromat and 100× NA1.30 Plan-Neofluar objectives and a Coolsnap HQ (Photometrics) camera. All fluorescence microscopes were controlled by Metamorph 7 (Molecular Devices). Images of larger tissue areas, e.g., for quantitative analysis of T cell infiltrates, were collected as tiled images using a DM4000, 20× NA0.70 HC PlanApo objective, and Coolsnap HQ2 controlled by custom journals with MetaMorph. Post-acquisition processing, including stitching of tiled images and quantitative analysis of signal intensity, was performed using Metamorph. T cell infiltrates were counted manually on tiled images. Mice. Donor female 129S6 and BALB/c mice were purchased from Taconic and the Jackson Laboratory, respectively. All mice were on a C57BL/6J (B6) background, and were bred and maintained at the University of Chicago, Brigham and Women’s Hospital, or Boston Children’s Hospital. B6 mice that express membrane-bound OVA on the surface of all cells (mOVA) were purchased from the Jackson Laboratory. B6 CD90.1/OT-I mice were generated from mice purchased from the Jackson Laboratory. MLCK210–/– and MLCKTg mice were developed as previously described (14, 29). MLCK210–/– mice (29) were backcrossed to B6 mice for 10 generations, and background was confirmed by high density SNP analyses. Transplantations. For allogeneic BMT, 5 × 106 bone marrow cells and 30 × 106 million splenocytes (minor mismatch BMT) or 5 × 106 bone marrow cells and 10 × 106 million splenocytes (major mismatch BMT) were given to age-matched, 7- to 12-week-old B6 recipients 24 hours after lethal irradiation (11 Gy). Antigen-specific GVHD was induced by i.v. injection of 5 × 106 bone marrow cells and 10 × 106 splenocytes from B6 WT mice and 2 × 106 B6 CD90.1/OT-I splenocytes into lethally irradiated B6 mOVA recipient mice. Mice were weighed and scored semiweekly. Disease activity was scored from 0 to 2 for posture, activity, fur texture, and hair loss, for a maximum score of 8. GVHD score was calculated by adding scores for weight loss relative to starting weight (>5%: 1; >7.5%: 2; >10%: 3; >12.5%: 4; >15%: 5) and disease activity (activity 1–3: 1; 4: 2; 5: 3; 6: 4; 7–8: 5) for a maximum total score of 10. Mice were sacrificed and considered dead of disease, i.e., deceased, if weight loss was greater than 20% or disease activity was greater than 7 for two consecutive measurements, as required by IACUC policies. Cytokine measurements. Serum or jejunal sections (0.5 cm) homogenized in cell lysis buffer (Bio-Rad) were assayed for IFN-γ, TNF, and IL-1β by ELISA using Ready-SET-Go! kits (eBioscience). MLCK210 transcript quantification. For MLCK210 mRNA quantification, jejunal epithelial cells were isolated using Matrigel Cell Recovery Solution (Corning), as described previously (71, 72). RNA was extracted using the RNeasy mini KIT (QIAGEN). After DNase treatment (Invitrogen), cDNA was generated using iScript RT supermix (Bio-Rad). SsoAdvanced Universal SYBR Green Supermix (Bio-Rad), primers against long Mylk (GCGTGATCAGCCTGTTCTTTCTAA, GCCCCATCTGCCCTTCTTTGACC) and Krt8 (AAGGTGTGGAAAGAGCTAGCC, ATAGACGTTGACTGCACGCACT), and a CFX96 real-time thermocycler (Bio-Rad) were used for detection. Raw data were analyzed by the ΔCt method, with Krt8 used for normalization. Changes were calculated by the ΔΔCt method. Intestinal and vascular permeability assays. Mice were denied access to food, but allowed water, for 3 hours before delivery of 12 mg FITC–4-kDa dextran or 0.25 mg free (unconjugated) fluorescein by oral gavage. Serum was collected after 3 hours and analyzed using a SynergyHT platereader (Bio-Tek) with 485 nm excitation and 528 nm emission. Data were normalized to age and sex-matched disease-free controls. For vascular permeability, 200 μg Alexa-647 BSA (Invitrogen) in 200 μl 0.9% saline was injected i.v. 30 minutes before mice were sacrificed. Segments (1.0 cm) of jejunum were fixed in 4% paraformaldehyde in PBS overnight, equilibrated in 30% sucrose, and snap-frozen in optimal cutting temperature (OCT) media. Thick (20 μm) cryosections were cut, mounted in SlowFade Diamond (Invitrogen), and imaged using a Leica DMI6000 inverted spinning disk (Yokogawa CSU-X1) confocal microscope with a 20× NA0.70 HC PlanApo objective and a Zyla 4.2 sCMOS camera (Andor) camera. Regions demonstrating well-oriented mucosal architecture, defined villi and crypts, and a visible vascular core within the villus were imaged as 15-μm-thick Z-stacks at 0.5-μm intervals. Sum projections were created using Metamorph and vascular dye retention calculated as mean intensity of the vascular core. Matched pseudocolor scales were applied for image presentation. Histopathology scoring. Histopathological analysis of GVHD target organs was performed by a subspecialty-trained gastrointestinal pathologist blinded to the experimental conditions. Jejunum, liver, and skin were scored from 0 to 3 at 0.5 intervals based on 4 features, for a maximum organ score of 12 and a maximum total score of 36 using previously reported criteria (4). Flow cytometry. Freshly isolated samples from lymph nodes and spleen were stained using PE-conjugated anti-CD90.1, FITC-conjugated anti-CD8, APC-conjugated anti-Vα2 (eBioscience), and BV510s-conjugated anti–granzyme B (BD). Flow cytometry was performed with a FACSCanto (BD) and analyzed with FlowJo. Statistics. All data presented are mean ± SEM. Statistical significance was determined by unpaired, 2-tailed t test, ANOVA with Bonferroni’s correction, 2-tailed Mann-Whitney U test, or Kaplan-Meier log-rank test. P values and the type of statistical analysis performed are described in the figure legends. In figures, *P < 0.05 and **P < 0.01. P < 0.05 was considered significant. Study approval. Studies of deidentified patient biopsies were approved by the University of Chicago Institutional Review Board. All experiments using mice were approved by and complied with regulations of the IACUCs of the University of Chicago, Brigham and Women’s Hospital, or Boston Children’s Hospital. Author contributions The project was conceived by SCN, PAS, and JRT. SCN, LZ, MLDMO, GS, AMW, WC, MCM, APS, KLE, GJB, NEJ, and JRT performed experiments. The manuscript was written and revised by SCN, PAS, and JRT with input from all authors. Figures were prepared by SCN and JRT. Acknowledgments We would like to thank the University of Chicago Human Tissue Resource Center for their expertise and assistance in recovery and IHC staining of human GVHD biopsies. This work was supported by NIH grants R01DK61931 (JRT), R01DK68271 (JRT), R24DK099803 (JRT), and R01AI110507 (PAS), and the Harvard Digestive Disease Center (P30DK034854). Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. License: Copyright 2019, American Society for Clinical Investigation. Reference information: J Clin Invest. https://doi.org/10.1172/JCI98554. References Ferrara JL, Smith CM, Sheets J, Reddy P, Serody JS. Altered homeostatic regulation of innate and adaptive immunity in lower gastrointestinal tract GVHD pathogenesis. J Clin Invest. 2017;127(7):2441–2451. View this article via: JCI PubMed CrossRef Google Scholar Clayburgh DR, et al. 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Review Free access | 10.1172/jci.insight.123947 Cutaneous immune responses mediated by dendritic cells and mast cells Tina L. Sumpter,1 Stephen C. Balmert,1 and Daniel H. Kaplan1,2 First published January 10, 2019 - More info Abstract In the skin, complex cellular networks maintain barrier function and immune homeostasis. Tightly regulated multicellular cascades are required to initiate innate and adaptive immune responses. Innate immune cells, particularly DCs and mast cells, are central to these networks. Early studies evaluated the function of these cells in isolation, but recent studies clearly demonstrate that cutaneous DCs (dermal DCs and Langerhans cells) physically interact with neighboring cells and are receptive to activation signals from surrounding cells, such as mast cells. These interactions amplify immune activation. In this review, we discuss the known functions of cutaneous DC populations and mast cells and recent studies highlighting their roles within cellular networks that determine cutaneous immune responses. Introduction In the skin, cellular networks maintain immune homeostasis and initiate protective innate and adaptive immune responses. DCs and mast cells are central within this network. Mast cells provide immediate innate immune signals to cells in the surrounding microenvironment. DCs, the most potent professional antigen-presenting cells, are essential for induction of adaptive immunity. However, the primary functions of DCs and mast cells are not achieved in isolation. Rather, initiation of innate and adaptive immune responses reflects intricate interactions between diverse cell types residing in the cutaneous microenvironment, including nonimmune cells such as keratinocytes and sensory nerve fibers. The cells forming the immune barrier in the skin have long been investigated independently, but recent focus has shifted toward understanding how these cells interact in context with one another and how their interactions facilitate coordinated innate and adaptive immune responses. In this review, we describe recent findings illustrating the importance of cellular networks in the skin. We highlight discoveries defining the physical interactions between the highly specialized epidermal Langerhans cells and their neighboring keratinocytes in relationship to adaptive immunity. We then discuss cellular interactions in the dermis, with a focus on dermal DCs and mast cells. Last, we discuss recent findings investigating the impact of cellular interactions between DCs or mast cells and a new player in innate immune responses, sensory nerve fibers. Collectively, these studies support the view that cellular interactions are critical for initiation of innate immune responses and subsequent adaptive immune responses in the skin. Interactions between Langerhans cells and keratinocytes The skin is anatomically divided into epidermis and dermis in mice and into epidermis, dermis, and hypodermis in humans. Langerhans cells, the sole professional antigen-presenting cells of the epidermis, are embedded within the stratum of tightly linked keratinocytes. The primary function of keratinocytes is to form a physical barrier. Keratinocytes are also armed with an arsenal of danger-sensing receptors, including pathogen recognition receptors TLR1-6 and TLR9 (1) and Ca2+ channels that detect perturbations in temperature, pressure, and osmotic regulation (2, 3). Upon activation, keratinocytes initiate immune responses, releasing antimicrobial peptides (β-defensins, REG3A, S100A7, and S100A8; ref. 4); cytokines (IL-6, TNF, IL-1α, IL-33, IL-36, and thymic stromal lymphopoietin [TSLP]; refs. 5, 6); and alarmins (high-mobility group protein box 1 and ATP; refs. 7, 8). Human, but not mouse keratinocytes, equipped with the NLRP1, NLRP3, and AIM2 inflammasomes, also cleave pro–IL-1β and pro–IL-18 into their active forms (9). Collectively, keratinocyte-derived cytokines initiate the sensations of itch and pain (10–13) and shape the outcome of immune responses by affecting the activation and migration of skin-resident immune cells. In the steady state, Langerhans cells are physically tethered to keratinocytes above the basal layer in the stratum spinosum. Epidermal retention of Langerhans cells requires TGF-β1 signaling (14). Latent TGF-β1 expressed on Langerhans cells is cleaved by keratinocyte-expressed integrins αvβ6 or αvβ8 (15), and keratinocyte-specific depletion of either αvβ6 or αvβ8 results in the loss of Langerhans cells in the epidermis (ref. 15 and Figure 1). Figure 1 Langerhans cells interact with keratinocytes in the epidermis through multiple junctions. In the steady state, the retention of Langerhans cells in the epidermis requires the conversion of TGF-β bound to the latency-associated peptide (LAP) to active TGF-β by integrins αvβ6 or αvβ8 expressed on the keratinocyte surface. Interactions between the epithelial cell adhesion molecule (EpCAM) on Langerhans cells and claudin-7, a variant of CD44, or epithelial cadherin (E-cadherin) expressed on keratinocytes may regulate Langerhans cell migration. DLN: draining lymph node. Illustrated by Mao Miyamoto. Langerhans cell maturation is promoted by pathogen-associated molecular patterns (16, 17), fragments of the ECM protein hyaluronan, as well as endogenous alarmins and cytokines produced by nearby keratinocytes (5, 18–20). Following activation, Langerhans cells extend dendrites through the tight junctions formed by keratinocytes in the stratum granulosum to acquire antigen. Langerhans cells, expressing the tight junction proteins claudin-1 and zonula occludens-1, form new tight junctions with keratinocytes (21). This mechanism allows Langerhans cells to sample antigen throughout the epidermis while maintaining keratinocyte barrier integrity. Activation-induced maturation causes epidermal Langerhans cells to migrate toward skin-draining lymph nodes (reviewed extensively in refs. 22, 23). Migration of Langerhans cells is a multistep process involving sequential upregulation of CXCR4 and CCR7 chemokine receptors (24). Migration from the epidermis appears to depend on the EpCAM, which mediates cell–cell contact via the tight junction protein claudin-7, a variant of CD44, or E-cadherin expressed on keratinocytes (ref. 25 and Figure 1). Langerhans cell–specific ablation of EpCAM increases Langerhans cell migration to skin-draining lymph nodes following topical application of the contact sensitizer 2,4,6-trinitrochlorobenzene, though this effect may be context dependent (26, 27). Increased CXCR4 expression promotes Langerhans cell migration from the epidermis toward CXCL12 secreted by dermal fibroblasts (24). As Langerhans cells arrive in the dermis and continue to mature, upregulation of CCR7 allows them to respond to CCL19 and CCL21 released by lymphatic endothelial cells and migrate through the lymphatics to draining lymph nodes (28). Immature Langerhans cells may also migrate to the dermis in response to CCL2 and CCL5 secreted by dermal fibroblasts triggered by chemical irritants (29). However, lack of CCR7 expression by immature Langerhans cells prevents subsequent migration to draining lymph nodes (29). Migration of DCs from the skin also depends on controlled ECM degradation by MMP-9, MMP-2, and hyaluronidase expressed by DCs, keratinocytes, and other cells in the dermis, such as fibroblasts (30–32). A major function of Langerhans cells is the delivery of processed antigen acquired in the skin to T cells in the lymph node to initiate adaptive immune responses. The precise function of Langerhans cells in the development of adaptive immunity, however, is not fully understood. The function of Langerhans cells has been best interrogated using mouse models in which Langerhans cells are depleted (recently reviewed elsewhere in ref. 33). For the contact hypersensitivity (CHS) model of allergic contact dermatitis, Langerhans cells are required only in the setting of very limited antigen density (14, 34–37). The bulk of the response is generated by cutaneous DC1s (cDC1s, classified in Table 1). During a Candida albicans infection, Langerhans cells are required for the development of protective Th17 responses and to reactivate skin-resident Th17 and Treg cells (38, 39). Table 1 Phenotypic classifications of cutaneous DCs in mice and the relationship with human cutaneous DC subsets In the dermis: dermal DC and mast cells Within the epidermis, regulation of Langerhans cell–keratinocyte junctions permits Langerhans cells to carry out their primary functions of antigen presentation and promoting T cell responses. Within the dermis, the primary functions of innate immune cells are more diversified. In the steady state, the ECM-rich dermis houses mast cells, innate lymphoid cells (ILCs), heterogeneous dermal DC populations, and migratory Langerhans cells (24, 29). Contact-dependent and contact-independent communication among dermal DCs, dermal mast cells, and other cells in the surrounding microenvironment affect complex immune processes, including antigen delivery to innate effector cells, antigen presentation to T cells, and activation of neural circuits. Dermal DCs. The primary function of dermal DCs, like that of their epidermal counterpart, Langerhans cells, is to deliver antigen to T cells. Several types of DCs have been identified within the skin and draining lymph nodes, and details regarding the phenotype, localization, and functional specialization of different DC subsets in mice and humans have been reviewed extensively (23, 33, 34, 40–42). Conventional DCs are typically located more superficially than dermal macrophages, which reside predominantly in deeper perivascular regions of the dermis (43, 44). Like Langerhans cells, dermal DCs acquire antigen within the skin and can present antigen both locally and in the skin-draining lymph nodes. Dermal DCs are grouped into multiple phenotypic categories with overlapping and distinct functions: cDC1s, cDC2s, DN DCs, and monocyte-derived DCs (ref. 23 and Table 1). The highest proportion of CD11b+ dermal DCs express CD301b (45). Genetic ablation strategies have been used to dissect the precise functions of dermal DC subsets in initiating adaptive immune responses. Transient depletion of CD301b+ dermal DCs reduces Th2 responses to the parasite Nippostrongylus brasiliensis or to protein antigens delivered with Th2-polarizing adjuvants (45–47) and reduces IL-17 responses in murine models of either psoriasiform dermatitis or Streptococcus pyogenes intranasal infection (48, 49). Studies evaluating mice constitutively or transiently deficient in the chemokine receptor XCR1 provide good insight into the general functions of dermal DCs in skin, although XCR1 is expressed in DCs in secondary lymphoid tissues and other peripheral tissues. Notably, inducible transient depletion of XCR1+ DCs impairs CD8+ T cell priming (50) and memory CD8+ T cell recall responses to secondary infection by intracellular pathogens (51). Mice constitutively lacking XCR1+ DCs have reduced numbers of intestinal T cells, which is attributed to diminished survival signals from XCR1+ DCs (52). Although conventional dermal DCs efficiently activate T cells in both the skin and draining lymph nodes, monocyte-derived dermal DCs, which have inferior migratory ability and somewhat reduced T cell stimulatory capacity, are still able to activate tissue-resident memory T cells, Tregs, or recruited effectors in the skin (53). Under various conditions (e.g., infection, allergen exposure), dermal DCs may recruit tissue-resident memory T cells from within the skin or central memory T cells from circulation by secreting chemokines, including CCL5, CCL18, CCL20, and CCL22 (54–58). In response to allergen challenge, dermal macrophages produce CXCL2 to recruit DCs and T cells to form clusters in perivascular regions of the skin (59). In all cases, the resulting clusters of DCs and T cells facilitate DC-mediated activation and proliferation of antigen-specific T cells in the skin. In addition to locally activating T cells within the skin, dermal DCs carry acquired antigen to skin-draining lymph nodes, which primes naive and memory T cell responses. Following antigen uptake, CCR7 upregulation facilitates dermal DC migration to the draining lymph nodes (28, 60) in a manner similar to that described for Langerhans cells. Like Langerhans cells, dermal DCs enzymatically cleave a conduit through the ECM to reach the lymphatics, a process that appears to depend, in part, on interactions with dermal fibroblasts. In vitro coculture experiments show that ICAM-1 and Thy-1 expressed on cutaneous fibroblasts associate with β2 integrin expressed on monocyte-derived DCs (61). During prolonged contact maintained by these cellular adhesion receptors, fibroblasts provide maturation cues to dermal DCs (62, 63). In particular, TNF-treated or IL-β–treated dermal fibroblasts induce expression of MMP9 by dermal DCs (61). Studies investigating the relationship between fibroblasts and dermal DCs in the context of nickel allergy demonstrate that nickel causes dermal fibroblasts to secrete IL-1β and CCL20, which promote DC maturation and recruitment of CD8+ T cells for cross-priming, respectively (64). Collectively, these interactions between dermal fibroblasts and DCs may remodel the ECM, allowing dermal DCs (and Langerhans cells) to travel through the dermis to the lymphatics to initiate T cell responses in skin-draining lymph nodes, as well as supporting local T cell activation in the skin. Mast cells. Mast cell functions are diverse, including remodeling of tissue and activation of neighboring cells through the release of inflammatory mediators. As such, the distance between mast cells and their neighbors dictates the magnitude of the effects of mast cell activation. Like DCs, cutaneous mast cells are found in the superficial dermis near blood vessels (44) and nerves (65). Mast cells are stimulated to secrete proinflammatory and Th2 cytokines, as well as amphiregulin (66) by bacterial and viral ligands (67); cytokines, including IL-9 (68), IL-33 (69), and TSLP (70); and neuropeptides (65), as well as IgE. Canonical mast cell activation initiated via the IgE/FcεRI pathway is well defined (reviewed in ref. 71). Perivascular mast cells extend processes through the vascular endothelium to sample the blood for IgE (72). Interactions between antigen-bound IgE and the FcεRI trigger immediate release of protease- and histamine-rich granules and heparin-stabilized cytokines (73). The protease content of mast cell granules differs in mice and humans. Murine granules contain chymases (mast cell protease [MCP] 4 and MCP5), tryptases (MCP6 and MCP7), and carboxypeptidase A3 (CPA3), while human connective tissue–type mast cell granules contain α/β1 and β2/β3 tryptase, chymase, and CPA3 (74). IgE also initiates de novo transcription of chemokines and cytokines, including TNF, IL-1β, IL-4, IL-9, and IL-13 and synthesis of lipid mediators, such as prostaglandin (PG) D2 and PGE2 (75). Released later than granules, these inflammatory mediators extend the duration of mast cell influence in the microenvironment. Mast cells are dynamic and have disparate functions in the skin. Releasing high levels of IL-4 and IL-13, mast cells are associated with atopy and Th2-skewed diseases (76, 77). Mast cells can also participate in Th17 responses (77, 78). In Th1-skewed immune responses, particularly in the murine models of CHS, mast cells have been shown to both exacerbate and mitigate immune responses (79–81). To resolve this discrepancy, mast cell functions in CHS were recently reevaluated using multiple lines of mast cell–deficient mice and different protocols to induce CHS (82). Mast cells suppressed the immune response in a chronic model of CHS whereas they were proinflammatory and increased immune sensitization using an acute CHS model (82). Surprisingly, in chronic CHS, 40% of mast cells transcribed antiinflammatory cytokine IL-10 following sensitization, and specifically depleting IL-10 in mast cells enhanced CHS (82). This important study resolved the seemingly conflicting results investigating the roles of mast cells in CHS, demonstrating that the roles of mast cells in complex cutaneous immune responses may differ based on the intensity of the reaction. Mast cells are positioned to interact closely with fibroblasts. In a murine fibrosis model, heterotypic ICAM-1/integrin interactions tether fibroblasts to mast cells. In this model, keratinocyte-derived plasminogen activator inhibitor 1 enhances mast cell accumulation in the tissue and increases mast cell–fibroblast contact. Mast cells provide IL-4, IL-13, and fibroblast growth factors that promote fibroblast proliferation (83, 84). Mast cell–derived histamine initiates collagen production from dermal fibroblasts (85). While mast cells stimulate fibroblasts in the skin, dermal fibroblasts secrete retinoic acid–degrading enzymes, which block expression of the P2RX7 (a receptor for ATP) by mast cells, impeding ATP-initiated mast cell activation (86). Thus, in some circumstances, interactions between dermal fibroblasts and mast cells have a net effect of homeostatic maintenance. Mast cells have also been identified in apposition to rare tissue-resident ILC2s in human and mouse skin (87). ILC2s are functionally similar to mast cells, with both cell types secreting IL-4, IL-5, IL-13, and amphiregulin following receptor-specific activation. Coordinated activation of mast cells and ILC2s may amplify protective antihelminth or damaging allergic inflammation. In the skin, ILC2s and mast cells physically associate through an as-yet-uncharacterized mechanism (87). ILC2s that are adjacent to mast cells are positioned to receive mast cell–derived activation signals. Human and mouse ILC2s are activated by IL-25, TSLP, and IL-33, which are released primarily by keratinocytes (88–90) but also by mast cells (69). In helminth infection in the gut, both mast cells and ILC2s accumulate, and IL-33, originating from ATP-stimulated mast cells, augments ILC2 activation (91). In the skin, where expression of P2RX7 is suppressed on mast cells (86), other mechanisms may regulate the ILC2/mast cell axis. For example, mast cell granules containing chymase and tryptase promote maturation of IL-33 (produced by mast cells or keratinocytes) into biologically active forms with enhanced potency. Compared with full-length IL-33, protease “edited” IL-33 more robustly expands ILC2 populations in vivo and activates ILC2s ex vivo (92). Through such mechanisms, the effect of mast cells on ILC2 activation and the production of type 2 cytokines may be additive and perpetuate inflammation in the skin. Interactions between mast cells and DCs in the skin Across multiple tissues from human and mice, mast cells directly interact with dermal DCs (93). IgE/antigen-activated mast cells maintain long-lasting contact with DCs via lymphocyte function-associated antigen 1 (LFA-1) and very late antigen 4 integrins (93). Contact between mast cells and DCs causes cytoplasmic reorientation, directing mast cell granule and cytokine release toward DCs and allowing transfer of IgE-bound antigens from mast cells to DCs (Figure 2). Mast cell/DC interactions alter local cytokine and chemokine production differentially depending on whether direct contact occurs (93). For example, in a contact-independent manner, mast cells cause DCs to reduce CCL2 and CCL3 secretion. Direct contact with mast cells prevents or delays this reduction. Coculture of bone marrow–derived DCs with peritoneal mast cells, but not mast cell–conditioned media, increased IFN-γ and IL-6 release, suggesting a contact-dependent effect (79). Collectively, these studies highlight the involvement of both paracrine and contact-mediated signaling between these cells. Figure 2 Dendritic cell–mast cell communication facilitates induction of adaptive immune responses. Contact-dependent and -independent mechanisms between DCs and mast cells (MCs) promote T cell responses. Illustrated by Mao Miyamoto. Notably, DCs modulate levels of membrane-bound TNF on the surface of mast cells. TNF, in turn, matures DC in a contact-dependent manner (81). Similarly, peritoneal-derived mast cells mature DCs in vitro (79). In the skin, mast cell–derived TNF has been shown to induce the migration of nearby dermal DCs to the skin-draining lymph nodes to prime T cells in models of allergic and irritant CHS (81, 94). Mast cell–derived TNF also modulates DC populations distal to the skin. Selective depletion of TNF in cutaneous mast cells diminishes the capacity of lymphoid resident (CD8+) DCs to prime T cells in the skin-draining lymph nodes (95). Through a mast cell intermediate, dermal DCs may regulate their own migratory path. Soluble mast cell–derived factors are also involved in activation-induced migration of Langerhans cells. Langerhans cell migration, like that of dermal DCs, is induced by TNF and IL-1β (96, 97). Langerhans cell migration in response to TLR2 or TLR7 ligands is dependent on TNF released from dermal mast cells (98, 99). In the course of allergic inflammation, other factors released by mast cells, including histamine, may direct Langerhans cell migration. Both human and mouse Langerhans cells express functional histamine receptors (100). In mouse models, FcεRI signaling in mast cells drives Langerhans cell migration to the skin-draining lymph node in a histamine-dependent manner (101). Antigen transfer and adaptive immune responses In conventional models of DC function, antigen is acquired directly from pathogens in the peripheral tissue; however, there are many examples in which DCs obtain antigen through less conventional means. DCs may deputize innate immune cells, stromal cells, or other DCs for professional antigen presentation via transfer of antigen–MHC II complexes. Dermal DCs (102, 103), lymph node–resident DCs (104–107), or lymph node stromal cells (108) can receive antigen–MHC II complexes from migrating Langerhans cells and dermal DCs. For example, Langerhans cells infected by herpes simplex virus in the epidermis migrate to the dermis, where they form clusters with dermal DCs, undergo apoptosis, and are phagocytosed by the dermal DCs, which then migrate to draining lymph nodes (102). Similarly, migratory DCs can transfer antigen to more abundant lymph node–resident DCs (104–107). A recent study demonstrated that cross-presentation of antigen from dying DCs and direct contact between DCs were not essential for antigen transfer but that LFA-1 expression on recipient DCs was required (104). Because LFA-1 is a scavenging receptor for DC-derived exosomes, exosome-mediated transfer of antigen is likely a predominant mechanism of antigen transfer between these DC populations (104). Antigen transfer from skin DCs enhances adaptive immune responses by disseminating antigen from a broader repertoire of DCs and by transfer of antigen from virally infected DCs with compromised antigen-processing capacity to uninfected DCs. Transfer of antigen–MHC II complexes from DCs to mast cells endows mast cells with antigen-presenting function. Recent studies have demonstrated direct transfer of MHC II from migratory DCs to mast cells (Figure 1), as well as to basophils in the dermis (109, 110). This process of MHC II–antigen transfer from DCs to mast cells occurs directly via immunological synapse-like contacts, a process known as trogocytosis. During skin inflammation (e.g., following topical application of hapten), mobile DCs form immune synapse-like contacts with stationary mast cells in the dermis, leading to transfer of plasma membrane (containing MHC II) from DCs to mast cells (110). These “cross-dressed” mast cells induce T cell proliferation and skew T cells toward the Th1 pathway (109). Through some combination of these contact-independent mechanisms and contact-dependent trogocytosis, skin-resident mast cells affect T cell responses in the skin-draining lymph nodes through a DC intermediate. Mast cells may initiate T cell activation using DC-acquired MHC II or with endogenous MHC II. Classical studies have shown that IFN-γ stimulation increases MHC II on the surface of immortalized human mast cells (111) and on human mast cells differentiated from peripheral blood (112). Moreover, it has recently been shown that IFN-γ–stimulated human skin–derived mast cells increase MHC II expression, acquire and process antigen, and induce T cell responses ex vivo (113). In humans, the exact location of mast cell/T cell interactions is unknown. In mice, mast cell migration to the skin-draining lymph nodes has been observed in a CHS model (114) and following ultraviolet irradiation (115). Mast cell function diverges in these models; in CHS, mast cells promote local inflammation and may promote T cell–mediated immunity in the lymph nodes. In ultraviolet radiation models, mast cells in the lymph node interact with B cells and diminish T cell responses. Collectively, these studies suggest that mast cells may act as antigen-presenting cells in the skin-draining lymph nodes. Mast cells also reportedly transfer endocytosed antigen-IgE-FcεR1 complexes to DCs through the synapse-like contact (93). DC recipients of mast cell–antigen-IgE complexes provide antigen-specific stimulation to T cells, resulting in T cell proliferation (93). The direct effects of antigen-IgE transfer from mast cells on the T cell–polarizing capacity of DCs were not evaluated in this particular study; however, other studies investigating the effects of “mast cell conditioning” on DCs have shown conflicting results. In vitro, mast cell–released histamine inhibits IL-12 expression in human DCs, blocking subsequent Th1 polarization and licensing the DC to polarize T cells toward a Th2 response (116, 117). However, DCs conditioned with mast cells have also been shown to skew T cells toward Th1 and Th17 phenotypes in vitro and in murine models of CHS and leishmaniasis (79, 81). The discrepancies in the reported outcomes of mast cell–DC communication on T cell skewing may reflect context-dependent differences in activation stimuli and in mouse models. Interactions with peripheral sensory nerve fibers Sensory afferent neurons modulate the functions of DCs and mast cells in antigen presentation and induction of innate inflammation. Myelinated nerve bundles, supported by Schwann cells, traverse vertically through the dermis (reviewed in refs. 118, 119). The nerve bundles lose their protective Schwann cells and terminate as either thinly myelinated Aδ or unmyelinated C-fibers in either the dermis or the epidermis. Nerve fibers react to physical or chemical stimuli, releasing neuropeptides and cytokines that modify the cutaneous microenvironment (65). Seminal work from Chui et al. (120, 121) demonstrated that sensory neurons are equipped to directly respond to bacterial infections in the skin and can serve as innate immune sensors. In addition, cutaneous afferents express receptors for many cytokines, such as TSLP, IL-4, IL-31, and IL-33 (11, 12, 122, 123). Thus, sensory afferents are able to directly detect pathogens and local inflammation-induced mediators, resulting in the transduction of pain and itch sensations. Keratinocyte-mediated nociceptive responses have been directly observed through optogenetic activation of keratinocytes engineered to respond to light, thereby resulting in activation of selective subsets of sensory neurons (13). Keratinocytes and other cellular sources of cytokines (mast cells, DCs, ILC2s) activate cutaneous afferents resulting in neuropeptide release into the microenvironment. Both Langerhans cells and dermal DCs associate with nerve fibers in the skin (124, 125). Depletion of Langerhans cells reduces the density of epidermal nerve fibers (126), demonstrating the relationship between these cell types. This relationship is not unidirectional because neuropeptides communicate with Langerhans cells to alter induction of Th1, Th2, and Th17 responses (127–129). Dermal DCs are adjacent to sensory fibers in the skin (125). In a recent study using the imiquimod model of psoriasis, blocking the activity of sensory nerve fibers inhibited IL-23 induction in dermal DCs and IL-17 production from dermal γδ T cells (125). Building on this finding, Kashem et al. (38) specifically linked release of the neuropeptide calcitonin gene-related peptide (CGRP) from C. albicans–sensing TRPV1-expressing cutaneous afferents to the IL-23 release from CD301b+ dermal DCs. Induction of IL-23, in turn, induced dermal γδ T cells to secrete IL-17A to control infection (38). Collectively, sensory nerves orchestrate local innate immune responses in the skin by modulating DC function. Mast cells form a physical synapse with unmyelinated C-fibers and are exquisitely poised for bidirectional communication with neurons in the skin (130–133). Mast cell–derived TNF and nerve growth factor (NGF) stimulate neuronal elongation (74, 134); mast cell–derived histamine interacts with pruriceptors on C-fibers to induce itch and substance P release (10). Although in vitro studies suggest that CGRP has no effect on mast cells, classic in vivo studies using the 2,4-dinitrofluorobenezene CHS model suggest that CGRP inhibits mast cell function (135, 136). Another neuropeptide, substance P, augments mast cell effector functions, acting through either the neurokinin-1 receptor or the members of the Mas-related GPCR family to amplify the mast cell response to IgE (137–139). Substance P synergizes with IL-33 to activate mast cells, increasing VEGF release and TNF synthesis (140, 141). Substance P alone induces mast cell degranulation (138, 142, 143). Interestingly, human mast cells stimulated with substance P alone release only PGD2, PGE2, and VEGF but not proinflammatory cytokines, such as TNF and IL-13. Generally, substance P induces a less robust mast cell response when compared with that initiated by IgE (138). Selective release of cytokines may limit immune responses and also cytokine-initiated neuronal sensations of itch or pain. How nerves contact innate immune cells in the skin is insufficiently studied. Sensory nerve fibers are equipped with multiple immune adhesive molecules. In culture, dorsal root ganglion cells express ICAM-1 and vascular cellular adhesion molecule 1 when activated with NGF (144). Notably, interactions between the immunoglobulin-like adhesion molecule nectin-3, which is expressed on neurons, and synaptic cellular adhesion molecule (SynCAM/Cadm1) expressed on a subset of mast cells have been reported (130, 131). Nectin-3/SynCAM interactions facilitate the close relationship between mast cells and neurons. At the RNA level, expression of Cadm1 is higher in cutaneous mast cells, compared with the expression of those isolated from the oral mucosa (tongue), and Cadm1 expression is higher than other cellular adhesion molecule family members and higher than FceR1a expression in skin mast cells (145), emphasizing the importance of this molecule in mast cell function. Though SynCAM expression has not been reported on cutaneous DCs, Langerhans cells also express Cadm1 mRNA, albeit at levels lower than that for Epcam and the TGF-β receptor subunits. These data suggest that Langerhans cells may be equipped with the molecules necessary to form a close physical association with sensory nerve fibers. Ultimately, adhesive junctions formed among DCs, mast cells, and sensory neurons may facilitate neuroimmune communication and, subsequently, alter the generation of protective innate immune responses in the skin. Conclusions There are many possibilities for future directions of research into cutaneous immune responses, along with some cautions to consider. A critical barrier in cutaneous research at this time is the lack of concordance between mouse skin– and human skin–bioinformatic studies; comparing human and mouse shows approximately 30% identity (146). Numerous differences between murine and human immunology (reviewed in ref. 147) emphasize the importance of translational studies to confirm that murine studies extend to humans. The integration of humanized mouse models into cutaneous immunology may resolve the human skin versus mouse skin issue. Bryce et al. (148) recently characterized mast cells in a humanized-mouse model. This type of model system provides a tool for manipulating human cells and their interactions in the skin. Our understanding of cutaneous immune responses and intercellular communication can be advanced by extrapolating findings in other barrier tissues (e.g., gut and lung). Similarly, novel mechanisms identified in the skin could also be extended — with experimental validation — to mucosal tissues. Identifying common and divergent pathways in skin and mucosal tissues may lead to broader application of existing therapeutics or development of new ones that target specific barrier tissues. Overall, it seems useful to view the complex series of interactions between innate immune cells in the skin as akin to molecular signaling pathways. Targeting upstream interactions may exert broad influence over downstream outcomes, while targeting downstream interactions may have more limited or specific effects. Just as mapping a molecular signaling pathway reveals potential targets for pharmacological intervention, understanding the complex series of cellular interactions in the skin provides insight into potential targets for manipulation to either enhance or suppress immune responses. Acknowledgments This manuscript was supported by National Institute of Arthritis and Musculoskeletal and Skin Diseases K01AR067250 to TLS, by National Cancer Institute T32CA175294 to SCB, and by National Institute of Arthritis and Musculoskeletal and Skin Diseases R01AR060744, R01AR067187, and R01AR071720 to DHK. Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. Published: January 10, 2019 Reference information: JCI Insight. 2019;4(1):e123947. https://doi.org/10.1172/jci.insight.123947. References Hari A, Flach TL, Shi Y, Mydlarski PR. Toll-like receptors: role in dermatological disease. Mediators Inflamm. 2010;2010:437246. 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Scooped by
Gilbert C FAURE
November 20, 2018 2:13 AM
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Objective Antimicrobial C-type lectin regenerating islet-derived 3 gamma (REG3G) is suppressed in the small intestine during chronic ethanol feeding. Our aim was to determine the mechanism that underlies REG3G suppression during experimental alcoholic liver disease.
Design Interleukin 22 (IL-22) regulates expression of REG3G. Therefore, we investigated the role of IL-22 in mice subjected to chronic-binge ethanol feeding (NIAAA model).
Results In a mouse model of alcoholic liver disease, we found that type 3 innate lymphoid cells produce lower levels of IL-22. Reduced IL-22 production was the result of ethanol-induced dysbiosis and lower intestinal levels of indole-3-acetic acid (IAA), a microbiota-derived ligand of the aryl hydrocarbon receptor (AHR), which regulates expression of IL-22. Importantly, faecal levels of IAA were also found to be lower in patients with alcoholic hepatitis compared with healthy controls. Supplementation to restore intestinal levels of IAA protected mice from ethanol-induced steatohepatitis by inducing intestinal expression of IL-22 and REG3G, which prevented translocation of bacteria to liver. We engineered Lactobacillus reuteri to produce IL-22 ( L. reuteri /IL-22) and fed them to mice along with the ethanol diet; these mice had reduced liver damage, inflammation and bacterial translocation to the liver compared with mice fed an isogenic control strain and upregulated expression of REG3G in intestine. However, L. reuteri /IL-22 did not reduce ethanol-induced liver disease in Reg3g–/– mice.
Conclusion Ethanol-associated dysbiosis reduces levels of IAA and activation of the AHR to decrease expression of IL-22 in the intestine, leading to reduced expression of REG3G; this results in bacterial translocation to the liver and steatohepatitis. Bacteria engineered to produce IL-22 induce expression of REG3G to reduce ethanol-induced steatohepatitis.
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Rescooped by
Gilbert C FAURE
from Immunology and Biotherapies
November 12, 2018 4:36 AM
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Abstract United airways disease (UAD) is the concept that the upper and lower airways, which are anatomically and immunologically related, form a single organ. According to this concept, upper and lower airway diseases are frequently comorbid because they reflect manifestations of a single underlying disease at different sites of the respiratory tract. Allergic asthma‐allergic rhinitis is the archetypal UAD, but emerging data indicate that UAD is a heterogeneous condition and consists of multiple phenotypes (observable clinical characteristics) and endotypes (pathobiologic mechanisms). The UAD paradigm also extends to myriad sinonasal diseases (eg, chronic rhinosinusitis with or without nasal polyps) and lower airway diseases (eg, bronchiectasis, chronic obstructive pulmonary disease). Here, we review currently known phenoendotypes of UAD and propose a “treatable traits” approach for the classification and management of UAD, wherein pathophysiological mechanisms and factors contributing to disease are identified and targeted for treatment. Treatable traits in UAD can be analyzed according to a framework comprising airway inflammation (eosinophilic, neutrophilic), impaired airway mucosal defense (impaired mucociliary clearance, antibody deficiency), and exogenous cofactors (allergic sensitizers, tobacco smoke, microbes). Appreciation of treatable traits is necessary in advancing the effort to deliver precise treatments and achieve better outcomes in patients with UAD. 1 INTRODUCTION The respiratory tract is divided into the upper and lower airways at the level of the vocal cords. Despite this artificial distinction, they are anatomically contiguous and immunologically related. United airways disease (UAD) is the concept that upper and lower airways form a single organ, with upper and lower airway diseases co‐occurring frequently because they reflect different manifestations of a single underlying disease process.1 Possible mechanisms linking the upper and lower airways include aspiration of nasal inflammatory cells and mediators into the tracheobronchial tree, hematogenous propagation of inflammatory mediators from one part of the airway to another, stimulation of bone marrow progenitor cells, or the nasobronchial reflex.2 The archetypal UAD is allergic asthma‐rhinitis, but emerging data indicate that UAD is complex and heterogenous, and may present with other clinical phenotypes of sinonasal disease (eg, chronic rhinosinusitis with or without nasal polyps) and lower airway disease (eg, bronchiectasis, chronic obstructive pulmonary disease [COPD]). Even within a given clinical phenotype, there is further variability based on the underlying pathobiologic mechanisms, known as endotypes. Current guideline‐based management approaches (summarized in Table 1) stratify patients according to symptoms, disease control, future risk, and occasionally broad clinical phenotypes, but do not sufficiently consider complexity and variability in other important dimensions such as airway inflammation, airway mucosal defense, and exogenous cofactors. Failure to recognize this complexity or treat both upper and lower compartments of the airways inevitably leads to suboptimal outcomes for patients. Site Disease Approach to stratification of patients and selection of therapies Patient stratification groups Recommended treatments according to patient stratification Other possible treatments Upper airway Allergic rhinitis Depends on symptoms, time course, severity, control, patient preferences, availability of treatment, and cost. One approach is a step‐up/step‐down approach based on assessment of control Step 1: mild symptoms Intranasal or oral non‐sedating H1‐antihistamines Leukotriene antagonists Allergen and irritant avoidance Allergen immunotherapy Nasal filters or saline Step 2: moderate‐to‐severe symptoms or persistent AR Intranasal corticosteroids Step 3: uncontrolled at step 2 (current or historical) Combination intranasal corticosteroids and intranasal H1‐antihistamines Step 4: uncontrolled at step 3 Short course oral steroids Chronic rhinosinusitis Based on clinical phenotype CRSsNP Intranasal corticosteroids Antibiotics (second line) Consider short course of oral steroids Saline irrigation Sinus surgery for medically refractory disease CRSwNP Intranasal corticosteroids Short course of oral steroids Antibiotic if suspicion of infection Consider leukotriene receptor for acetylsalicylic acid sensitivity Lower airway Asthma Assessment of symptoms, exacerbations, and lung function followed by stepwise escalation/de‐escalation of therapy Step 1 Consider low‐dose ICS Leukotriene receptor antagonists Theophylline Allergen avoidance Allergen immunotherapy for patients with allergic rhinitis and sensitized to house dust mites, frequent exacerbations, and FEV1 > 70% Vaccinations Weight reduction for obese asthma patients Step 2 Low‐dose ICS Step 3 Low‐dose ICS + LABA Step 4 Medium‐/high‐dose ICS + LABA Step 5 Low‐dose oral corticosteroids Add‐on treatments: tiotropium, anti‐IgE, anti‐IL5, bronchial thermoplasty Patients may benefit from phenotyping and endotyping at Step 5 Chronic obstructive pulmonary disease Assessment of symptoms (CAT, mMRC), exacerbations, airflow obstruction (FEV1) Group A (CAT < 10, mMRC < 2, infrequent exacerbations) Bronchodilator Smoking cessation (including pharmacologic treatment) Education, self‐management, and pulmonary rehabilitation Pneumococcal and influenza vaccinations Long‐term oxygen therapy in the presence of severe resting hypoxemia Long‐term noninvasive ventilation for patients with severe chronic hypercapnia and a history of hospitalization for acute respiratory failure Bronchoscopic or surgical lung volume reduction surgery for selected patients Group B (CAT ≥ 10, mMRC ≥ 2, infrequent exacerbations) LABA or LAMA Increase to LAMA + LABA if persistent symptoms Group C (CAT < 10, mMRC < 2, frequent exacerbations) LAMA Increase to LAMA + LABA or change to LABA + ICS if further exacerbations Group D (CAT ≥ 10, mMRC ≥ 2, frequent exacerbations) LAMA + LABA Increase to LAMA + LABA + ICS if persistent symptoms/further exacerbations Consider macrolides Consider roflumilast if FEV1 < 50% predicted and patient has chronic bronchitis Bronchiectasis Assessment of microbial infection, exacerbations and airway symptoms Pseudomonas aeruginosa infection with frequent exacerbations Long‐term inhaled antibiotic treatment Escalate to combined oral and inhaled antibiotic treatment if inadequate response Physiotherapy, pulmonary rehabilitation, and/or airway clearance Pneumococcal and influenza vaccinations Long‐acting bronchodilators for patients with significant breathlessness Non‐Pseudomonas aeruginosa infection with frequent exacerbations Long‐term macrolide treatment Escalate to combined oral and inhaled antibiotic treatment if inadequate response Multiple sequential airway treatments Short‐ or long‐acting bronchodilators → Mucolytic/physiotherapy adjuncts → airway clearance → inhaled antibiotics AR, allergic rhinitis; CAT, COPD Assessment Tool; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps; FEV1, forced expiratory volume in one second; ICS, inhaled corticosteroids; ICS + LABA, combination inhaled corticosteroids and long‐acting beta agonist; LABA, long‐acting beta agonist; LAMA, long‐acting muscarinic antagonist; mMRC, modified Medical Research Council dyspnea score. The treatable traits approach has been described for lower airway diseases,3 and in this review, we extend its application to combined upper and lower airway disease. We summarize the current evidence for known clinicopathobiologic subtypes (“phenoendotypes”) of UAD. We have grouped the clinical manifestations of UAD according to the “treatable traits” of airway inflammation, airway mucosal defense dysfunction, and exogenous cofactors (Figure 1 and Table 2). These traits are not mutually exclusive and multiple traits may contribute to disease in an individual at any one point in time. Treatable traits may also vary over time. It is with the intention of drawing the readers’ attention to traits that are common to both airway compartments that we have artificially classified the upper and lower airway conditions as presented in this review. We believe that targeting common disease processes, when used in combination with current patient stratification approaches, is likely to lead to clinical improvements at both sites of the respiratory tract. Trait Endotype/pathophysiology Method of assessment/biomarker Clinical phenotype Targeted treatment Upper airway Lower airway Inflammation Eosinophilic, high type 2/TH2‐cytokines IL‐4, IL‐5, IL‐13 Blood periostin, high FeNO, sputum eosinophilia, blood eosinophilia CRSwNP Eosinophilic asthma Corticosteroids (systemic, inhaled, intranasal), anti‐IL‐5, IL‐4, IL‐13, anti‐TSLP, ?CRTh2 antagonist Allergic, systemic CD4+ TH2 cells Blood total IgE, blood specific IgEs, skin prick tests Allergic rhinitis Allergic asthma Allergen avoidance, corticosteroids, antileukotrienes, anti‐IgE, immunotherapy Allergic, local Local nasal and bronchial mucosa specific IgE production Blood total IgE not raised, negative blood specific IgEs, negative skin prick tests, local IgE and specific IgE production, nasal allergen provocation test Local allergic rhinitis Intrinsic asthma ?Omalizumab, ?immunotherapy Non‐allergic eosinophilic IL‐25, IL‐33, TSLP, group 2 innate lymphoid cells Blood periostin, high FeNO, sputum eosinophilia, blood eosinophilia, non‐reactive skin prick tests, absent specific IgE in blood Non‐allergic rhinitis with eosinophilia syndrome (NARES) Adult onset eosinophilic asthma Anti‐TSLP, anti‐IL‐4, IL‐5, IL‐13, ?CRTh2 antagonist Neutrophilic TH17 cells, IL‐17, CXCL1, CXCL8 IL‐8, sputum neutrophilia CRSsNP COPD, neutrophilic asthma Smoking cessation, macrolides Impaired airway mucosal defense Cystic fibrosis Autosomal recessive disorder in CFTR gene leading to improper salt balance and viscous airway surface liquid Genetic testing, sweat chloride test CRSwNP (acid mucin) Bronchiectasis CFTR modulators Primary ciliary dyskinesia Autosomal recessive mutations causing dynein and radial spoke defects Low nasal nitric oxide, ciliary motion and ultrastructure CRSsNP Bronchiectasis No validated PCD‐specific therapies Primary antibody deficiency Deficient immunoglobulins or functional antibody response Quantitative serum immunoglobulin levels, functional antibody responses CRS Bronchiectasis Immunoglobulins, vaccinations Exogenous cofactors Occupational exposures High molecular weight sensitizers: IgE‐mediated type 2 inflammation Low molecular weight sensitizers: haptens Irritant‐induced: no immunological reaction Total IgE, skin prick tests Peak flow monitoring Specific bronchoprovocation challenge Occupational rhinitis, reactive upper airways dysfunction syndrome Occupational asthma, reactive airways dysfunction syndrome Exposure avoidance, respiratory protection devices, ?anti‐IgE Aspirin/non‐steroidal anti‐inflammatories Constitutive overexpression of 5‐lipoxygenase and leukotriene C4 synthase Aspirin/NSAID challenge, urinary leukotriene E4 CRSwNP Severe asthma Avoidance, desensitization, antileukotrienes Staphylococcus aureus enterotoxin Superantigens elicit Th1, Th17 and Th2 cytokines, including IL‐4, IL‐5, IL‐13 Staph aureus enterotoxin IgE's CRSwNP Severe asthma ?anti‐IgE Aspergillus/fungal hypersensitivity TH2 cells, IL‐4, IL‐5, IL‐13, IgE, eosinophilia Aspergillus skin test positivity, Aspergillus specific IgE, IgE > 1000 IU/mL, Blood eosinophil >500/μL, precipitating antibodies to Aspergillus Allergic fungal rhinosinusitis Allergic bronchopulmonary aspergillosis (asthma, bronchiectasis) Steroids, antifungal, ?anti‐IgE Upper respiratory tract infection Variable depending on microbe and underlying disease Respiratory cultures and nucleic acid tests Exacerbation of rhinitis/rhinosinusitis Exacerbation of asthma, COPD or bronchiectasis Antivirals, antibiotics, vaccinations Typical upper and lower airway clinical phenotypes associated with underlying treatable traits are listed. Taxonomy based on clinical phenotypes has significant limitations: each phenotype may represent comprise treatable traits, for example, CRSwNP and asthma may be neutrophilic or eosinophilic inflammation depending on the population studied. Hence, a more precise approach is needed to identify contributory treatable trait(s) in each case, which can aid in selection of targeted treatments. Question mark (?) indicates targeted therapies under investigation. Treatable traits and targeted therapies may be used to complement the current approaches for patient stratification and treatment selection—including non‐targeted treatments—shown in Table 1. 2 AIRWAY INFLAMMATION Airway inflammation is important in the pathogenesis of many upper and lower airway diseases. It is a dynamic trait which varies over time and is modulated by factors such as treatment, infection, environmental exposures, and natural history of disease.4 Clinicians commonly assume that asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) are stereotypically eosinophilic in nature, and that chronic rhinosinusitis without nasal polyps (CRSsNP) or COPD is stereotypically neutrophilic. As discussed below, while these generalizations may hold true for many cases there is substantial variability in the underlying pathophysiological mechanisms for each clinical phenotype or disease. Identification and quantification of airway inflammation can help to direct appropriate treatment. Current methods to assess upper and lower airway inflammation are summarized in Table 3. Method Comments Strengths Limitations Nasal lavage Luminal proteins, cytokines and cells Simple and safe Correlates with, but less invasive than induced sputum Variable fluid recovery and dilution with lavages No sampling of the epithelium Nasal brush or scraping Samples the nasal epithelium Simple and minimally invasive Does not sample deeper layers of the mucosa or the nasal lumen Nasal biopsy Identifies tissue inflammatory cellular subtypes of rhinitis or rhinosinusitis Samples the total nasal mucosa Technically difficult No information about nasal lumen Blood periostin Marker of Th2, eosinophilic airway inflammation Predicts severity of chronic rhinosinusitis Predicts chronic rhinosinusitis with nasal polyps phenotype Noninvasive Not widely available Conflicting evidence on whether periostin is associated with sputum eosinophilia Sputum induction Neutrophil count ≥65% or >500 × 104/mL identifies neutrophilic airway inflammation Eosinophil count ≥3% identifies eosinophilic airway inflammation Noninvasive Well‐validated Not widely available Logistically, technically and practically difficult High failure rate Risk of inducing bronchoconstriction Peripheral blood eosinophils Eosinophil count ≥2% identifies eosinophilic airway inflammation Noninvasive, minimal risk Widely available, cheap Predicts with important clinical outcomes such as exacerbation risk and response to treatment Wide diurnal variation of readings (40%) within the same subject May not be applicable when only local mucosal inflammation occurs Fractional exhaled nitric oxide (FeNO) FeNO < 25 ppb indicates low likelihood of airway eosinophilia FeNO > 47 ppb suggests eosinophilic airway inflammation and corticosteroid responsiveness Noninvasive Quick, easy, and safe to perform Readings may be affected by smoking, respiratory tract infections Sputum eosinophilia and FeNO are not always concordant Urinary leukotriene E4 (LTE4) Marker of cysteinyl leukotriene activity Higher levels observed in aspirin‐exacerbated respiratory disease Collection of urine is simple and of no risk Special equipment and training are required to measure LTE4 2.1 Allergic asthma‐rhinitis The link between allergic asthma and allergic rhinitis (AR) is well established. Up to 40% of AR patients have asthma and almost all patients with asthma have AR.5 Many patients with AR also exhibit nonspecific bronchial hyperresponsiveness.6 IgE‐mediated hypersensitivity to aeroallergens results in type 2/eosinophilic inflammation in the respiratory tract, manifesting as rhinitis in the upper airways and asthma in the lower airways. Upon allergen exposure, sensitization occurs whereby specific IgE (sIgE) are generated, circulate in the blood, and attach to the surface of mast cells and basophils, including those that reside in the airway mucosa. Subsequent exposure to allergen triggers mast cells degranulation, release of chemical mediators, and synthesis of leukotrienes and cytokines, resulting in an immediate allergic airway reaction. The late phase response involves Th2 lymphocyte recruitment with production of inflammatory cytokines such as IL‐4, IL‐5, and IL‐13, as well as activation of eosinophils. The central role of sIgE in allergic asthma‐rhinitis is highlighted by a population‐based birth cohort study showing that presence of peripheral blood sIgE directed against common allergens is associated with increased odds of asthma and rhinitis in childhood.7 In adults with AR, experimental nasal provocation with house dust mite allergens induces not only nasal eosinophilia but also bronchial eosinophilic inflammation, bronchoconstriction, and bronchial hyperresponsiveness,8 suggesting inflammatory crosstalk between upper and lower airways. The allergic asthma‐rhinitis phenoendotype usually begins in childhood and can be identified by measuring peripheral blood total IgE which is elevated, plus demonstration of atopy by the presence of raised sIgE levels in blood or skin prick test positivity. Omalizumab, an anti‐IgE monoclonal antibody, is efficacious for both severe allergic asthma9 and uncontrolled AR.10 Therapeutic response to omalizumab is predicted by higher baseline periostin levels and reduced free serum IgE levels during period of treatment.11 In some cases, specific causative allergens can be identified and targeted with allergen immunotherapy. In both AR12 and allergic asthma,13 immunotherapy improves symptoms and reduces the need for pharmacotherapy in the short term, albeit with limited evidence for longer‐term efficacy. Treatment of AR patients with grass pollen sublingual immunotherapy tablets was associated with slower AR progression, less frequent asthma onset, and slower asthma progression.14 Candidate biomarkers that can identify and/or predict response to allergen immunotherapy include the sIgE:total IgE ratio, specific IgG4 and IgE‐FAB.15 2.2 Local allergic rhinitis‐non‐allergic asthma: local mucosal IgE production A subset of asthma and rhinitis patients demonstrate type 2/eosinophilic allergic airway responses mediated by sIgE which is produced and sequestered in the airway mucosa, with skin prick test non‐reactivity and no detectable circulating sIgE in peripheral blood. In the upper airway, this phenoendotype is known as local allergic rhinitis (LAR), a distinct entity characterized by local production of sIgE in the nasal mucosa without evidence of systemic atopy. LAR does not appear to represent a forme fruste of AR,16 and is associated with increased risk of asthma compared to healthy individuals without LAR.17 The lower airway analog of LAR may correspond to a subtype of non‐allergic asthma which is currently not well defined, but whose existence is supported by studies (Supporting Information: References S1‐S4). In the aforementioned entity, intramucosal IgE synthesis is observed in the lower airways, and functional sIgE can be found in the sputum despite negative skin prick tests and blood sIgE levels. Bronchial inhalational challenge with allergen induces a clinical lower airway allergic response characterized by sputum eosinophilia and bronchial hyperresponsiveness. It is not known why individuals with allergic asthma‐rhinitis demonstrate positive skin prick tests and elevated sIgE in blood, whereas non‐allergic asthmatics and patients with LAR do not although local mucosal IgE synthesis occurs in all those conditions. One possibility is that local mucosal IgE synthesis may not reach sufficient quantities to spill over into peripheral blood. Alternatively, IgE may be sequestered within the bronchial mucosa. Regardless, efficacy of omalizumab has been shown in non‐atopic asthma with evidence of local mucosal IgE production. Pillai et al. (Supporting Information: References S5) randomized 18 such subjects and obtained bronchial biopsies from subjects before and after treatment with 12‐14 weeks of omalizumab. The patients subsequently underwent supervised dose reduction of their regular asthma therapy. Compared to placebo, omalizumab therapy significantly reduced total bronchial mucosal IgE+ cells. Lung function declined in the placebo‐treated group but improved in the omalizumab‐treated group. This small but important study serves as proof‐of‐concept that anti‐IgE can target disease associated with local mucosal IgE production. 2.3 Non‐allergic rhinitis with eosinophilia syndrome‐non‐allergic eosinophilic asthma Type 2 (eosinophilic) inflammation can occur in UAD without evidence of IgE‐mediated hypersensitivity. In the upper airways, this endotype has been termed non‐allergic rhinitis with eosinophilia syndrome (NARES) and is characterized by persistent rhinitis and marked eosinophilia of the nasal mucosa in the absence of local or systemic IgE production, suggesting allergen‐independent induction of eosinophilic airway inflammation.18 Almost half of patients with NARES who do not report asthmatic symptoms nevertheless demonstrate bronchial hyperresponsiveness and sputum eosinophilia, supporting a link between NARES and asthma.19 The corresponding asthma phenoendotype is non‐allergic eosinophilic asthma, in which eosinophilic inflammation and type 2 cytokine production are not driven by allergen‐activated Th2 lymphocytes, but is instead postulated to be initiated by type 2 innate lymphoid cells (ILC2).20 ILC2s are a recently discovered population of lymphocytes capable of producing large amounts of type 2 cytokines (IL‐5 and IL‐13) and orchestrate eosinophilic inflammation in the absence of adaptive immunity, including Th2 cells, B cells, and IgE antibody.21 ILC2s are activated by epithelium‐derived cytokines IL‐25, IL‐33, and thymic stromal lymphopoietins (TSLP), which are released by epithelial cells in response to epithelial damage caused by a wide range of stimuli including microbiota and pollutants. ILC2s are increased in peripheral blood in eosinophilic asthmatics compared to non‐eosinophilic asthmatics and their numbers in sputum correlate with eosinophil counts.22 Increased ILC2s has also been observed in eosinophilic nasal polyps,23 but evidence for the involvement of ILC2 cells in NARES and non‐allergic eosinophilic asthma is lacking and should be the focus of future studies. Potential targeted treatments for this pathway include monoclonal antibodies targeting any of the type 2 cytokines, discussed in the section below. TSLP, targeted by the monoclonal antibody tezepelumab, was shown in a recent dose‐ranging proof‐of‐concept study to reduce exacerbations in patients with uncontrolled asthma, including in those with low IgE (<100 IU/mL).24 Antagonists of CRTH2, the receptor for prostaglandin D2 on ILC2 cells, are currently undergoing evaluation to assess clinical efficacy (Supporting Information: References S6, S7). 2.4 Asthma‐chronic rhinosinusitis Chronic rhinosinusitis (CRS) is broadly defined as an inflammatory disorder of the paranasal sinuses and mucosa of the nasal passages that lasts 12 weeks or longer. The condition is heterogeneous, with 2 broad clinical phenotypes, with nasal polyps (CRSwNP) and without nasal polyps (CRSsNP), as well as diverse endotypes.25 Epidemiologic studies have demonstrated higher prevalence of CRS in asthmatics compared to non‐asthmatics across different populations.26, 27 However, the inflammatory endotype of CRS varies according to the population being studied. In Caucasian subjects, CRSwNP is predominantly eosinophilic and CRSsNP is predominantly neutrophilic, whereas in Chinese subjects CRSwNP is mainly neutrophilic, with fewer Chinese subjects demonstrating eosinophilic nasal polyps.28 Various studies have elucidated the detailed phenoendotypes of either CRS or asthma separately, but there is a paucity of data about phenoendotypes of combined asthma‐CRS. Despite this, phenoendotypes of asthma and CRS are remarkably analogous to each other. Based on sputum inflammatory cells, asthma can be eosinophilic, neutrophilic, mixed eosinophilic and neutrophilic, or paucigranulocytic.29 Based on bronchoepithelial cell gene expression profiles, asthma inflammatory signatures can be partitioned into “Th2 high” (associated with elevated IL‐4, IL‐5, IL‐13, sputum, and blood eosinophilia) or “Th2 low”.30 CRS endotypes can be similarly classified into “IL‐5 high” and “IL‐5 low” clusters.31 Subjects with IL‐5 high CRS have high eosinophilic cationic protein and IgE from nasal specimens, and present clinically with CRSwNP and asthma. Low IL‐5 clusters clinically exhibit the CRSsNP phenotype. “IL‐5 high” CRS appears to be the upper airway analog of “Th2‐high” asthma. The inflammatory pattern of the upper and lower airways in patients with nasal polyps and comorbid asthma was evaluated in a recent study using nasal polyp biopsies and exhaled nitric oxide.32 Approximately, two‐thirds of patients were eosinophilic and one‐third was non‐eosinophilic, with concordance demonstrated between the upper and lower airways in individual subjects. More studies are needed to clarify concordance between upper and lower airway phenoendotypes across the spectrum of inflammatory endotypes in asthma and CRS. Systemic, inhaled, or intranasal corticosteroids are cost‐effective treatments for eosinophilic upper and lower airway inflammation. In cases that are refractory to corticosteroids or in patients who are unable to tolerate high doses of corticosteroids, several biologics targeting eosinophilic inflammation can be considered, such as anti‐IL‐13 (tralokinumab), anti‐IL‐5 (mepolizumab and reslizumab), antibodies against alpha chain of IL‐5 receptor (benralizumab), and alpha subunit of the IL‐4 receptor (dupilumab). Mepolizumab is efficacious in both eosinophilic nasal polyposis and severe eosinophilic asthma,33, 34 reducing polyp burden and need for surgery in the former and reducing exacerbations in the latter. Similarly, dupilumab was demonstrated in small phase 2 trials to reduce polyp burden in patients with chronic sinusitis and nasal polyposis,35 and was found to decrease exacerbations and improve forced expiratory volume in one second (FEV1) in patients with severe eosinophilic asthma.36 Patients with asthma and nasal polyps show greater improvement in Asthma Control Questionnaire score with reslizumab compared to asthmatics without nasal polyps.37 2.5 Chronic obstructive pulmonary disease‐chronic rhinosinusitis Chronic obstructive pulmonary disease is a disease characterized by chronic respiratory symptoms and persistent airflow limitation caused by significant exposure to noxious particles or gases, most commonly tobacco smoke. Although COPD has traditionally been thought to be a purely lower airway disease, there is increasing evidence to suggest frequent concomitant involvement of the upper airways. Multiple epidemiologic studies have shown a high prevalence of nasal symptoms among COPD patients. An early population‐based epidemiologic study conducted in the Swedish general population in 1992 found that 40.1% of individuals with self‐reported chronic bronchitis or emphysema had symptoms of rhinosinusitis, compared with 32.7% in the total study sample.38 In a follow‐up study in 2000, those who reported thick, yellow, nasal discharge and nasal blockage in 1992 had a higher incidence of COPD diagnosis over an 8‐year follow‐up period.39 Another cross‐sectional population‐based Canadian study also found an association between CRS and COPD, both self‐reported.40 Self‐report may lead to misclassification errors of COPD and sinonasal disease but are an inherent limitation of large‐scale epidemiologic studies. Medical record diagnoses, which are considered more reliable than self‐reported medical history, were used in one study from Taiwan which extracted International Classification of Diseases diagnostic codes from a national insurance database and found an increased risk of CRSsNP among COPD patients.41 Recent studies have utilized more stringent and objective criteria for classifying COPD and rhinosinusitis. Bergqvist et al.42 used spirometry for identifying COPD, defined as FEV1/forced vital capacity (FVC) ratio <0.7, and found that the 5‐year incidence of nasal symptoms without having a cold was higher in subjects who demonstrated obstruction on spirometry compared to subjects without baseline spirometric evidence of airflow limitation. Hansen et al43 evaluated the prevalence of paranasal sinus opacification at magnetic resonance imaging in COPD and asthma patients compared to a control group. COPD was defined using similar spirometric criteria as the Bergqvist et al study, whereas asthma was self‐reported. COPD and asthma patients were, respectively, found to be 6 and 2 times more likely than healthy controls to demonstrate paranasal sinus opacification. These findings support the link between upper and lower airway diseases in both asthma and COPD, but we cannot conclude from this study that the association with sinonasal disease is stronger for COPD than for asthma because misclassification bias may have occurred among asthma patients, who were diagnosed based on self‐report instead of objective evidence of variable airflow limitation. Similarly, uncontrolled COPD cohort studies have also found a high prevalence of up to 75% of sinonasal disease, when using spirometry for COPD diagnosis and CT paranasal sinuses for diagnosis of CRS.44, 45 An important limitation of all the aforementioned studies is the use of prebronchodilator, instead of postbronchodilator, FEV1/FVC ratio for identifying cases of COPD. Such a definition could result in other obstructive lung diseases (such as asthma or bronchiectasis) being misclassified as COPD. Only one small study thus far has evaluated COPD using postbronchodilator spirometry and found higher nasal symptoms scored on a visual analogue scale compared to healthy age‐matched controls.46 Although prevalence of sinonasal disease does not increase with declining FEV1,44, 45 the presence of sinonasal disease has profound effects on other important COPD‐related outcomes such as symptom morbidity and exacerbations, which are known to be relatively independent of FEV1. Upper airway symptoms worsen over the natural history of COPD,47 and are associated with lower airway symptoms44 and impaired quality of life.48 Sinonasal symptoms also feature prominently during COPD exacerbations, and are associated with frequent exacerbations47 as well as treatment failure of acute exacerbation of COPD.49 Tobacco smoke forms the common link between COPD and CRS,50 likely by inducing neutrophilic inflammation in the nasal and bronchial mucosa. Compared with non‐smoking healthy controls, smokers without COPD present with nasal inflammation characterized by increased neutrophils and CD8 T lymphocytes51 although this has not been consistently demonstrated.52 Nasal and bronchial IL‐8 levels, neutrophil counts, and CD8 Th1 cells are even higher in smoking COPD patients than in smoking “healthy” controls matched for pack‐year smoking history.51, 53 Nasal and sputum IL‐8 concentrations correlate in COPD patients,53 indicating concordance of neutrophilic inflammation between upper and lower airways in keeping with the UAD hypothesis. Release of neutrophil‐derived proteases such as elastase and matrix metalloproteinase‐9 causes alveolar wall destruction and mucous hypersecretion characteristic of COPD, and may contribute to tissue destruction and remodeling of the sinonasal mucosa seen in CRS. Neutrophilic inflammation results in airflow limitation in the lower airways in COPD, which is mirrored in the upper airways by reduced nasal patency54 and higher nasal resistance.55 Severity of lower airway obstruction, as measured by FEV1, correlates with severity of CRS symptoms.45 Smoking cessation alters the progressive clinical course of COPD by reducing lung function decline and mortality, hence remaining a cornerstone of COPD treatment in addition to other medical therapies. Additionally, in CRS, smoking cessation improves symptoms, quality of life and decreases CRS‐related antibiotic use.56Neutrophilic airway inflammation per se may potentially be targeted for treatment using macrolides, which exert a repertory of effects that suppress neutrophilic inflammation, including downregulation of IL‐8, elastase and matrix metalloproteinase‐9, and reduction of neutrophil chemotaxis and survival.57 Macrolides have proven efficacy in decreasing the frequency of COPD exacerbations,58 and in a small double‐blind randomized controlled trial was associated with improvement in symptoms, endoscopic scores, and nasal lavage IL‐8 levels specifically in Th1, neutrophilic CRS patients.59 Further studies are needed to confirm the efficacy of macrolides. In addition, long‐term macrolides should only be used in carefully selected patients after optimization of other standard medical therapies because of potential cardiac and otological adverse effects, as well as risk of inducing antibiotic resistance. 3 IMPAIRED AIRWAY MUCOSAL DEFENCE Major components of the airway mucosal defense mechanism include the mucociliary escalator, immunoglobulins, antimicrobial peptides, the epithelial barrier, and cells of the innate and adaptive immune system. Impaired mucosal airway defense has a causal role in several phenoendotypes of UAD. The predominant lower airway phenotype in UAD due to impaired mucosal defense is bronchiectasis, which is characterized by abnormal and irreversible dilatation of the lower airways. Frequent coexistence of bronchiectasis and sinonasal disease has long been recognized.60 Patients with bronchiectasis have a high prevalence of CRS when assessed using European Position Paper on Rhinosinusitis and Nasal Polyps criteria, that is, presence of symptoms and positive findings on either nasoendoscopy or CT of paranasal sinuses.61, 62 Conversely, patients with CRS more frequently demonstrate CT evidence of dilated airways compared to individuals without CRS.63 3.1 Cystic fibrosis: bronchiectasis‐chronic rhinosinusitis due to airway surface liquid viscosity Airway surface liquid (ASL) viscosity is regulated in part by the cystic fibrosis transmembrane regulator (CFTR) protein, which mediates ion transport at the airway epithelial surface. Pathological processes which impair CFTR activity can result in abnormal ion flux at the epithelial surface, increased sodium reabsorption, periciliary liquid depletion, and increased mucous viscosity, thereby impairing mucociliary clearance.64 Loss of CFTR‐mediated bicarbonate secretion in the airway epithelium also results in acidification of the ASL, which impairs the action of antimicrobial peptides in the ASL, rendering the airway more susceptible to colonization and infection by microbes.64 Cystic fibrosis (CF) is due to heterogeneous autosomal recessive mutations in the CFTR gene and affects mucociliary clearance at the sinoepithelial lining, lower airways, gastrointestinal tract, and exocrine organs. Sinonasal disease is ubiquitous in CF and characterized by neutrophilic polyps with acid mucin glands, mucoceles, or pseudomucoceles.65 Lower airway disease is characterized by intense neutrophilic inflammation resulting in bronchiectasis, which occurs in 70%‐75% of children by 5 years of age and represents the major cause of morbidity and death in this condition. Treatment of CF has been transformed by the discovery of novel CFTR modulators aimed at addressing the specific defects causing reduced CFTR activity. The most common gene mutation in CF is F508del which causes a processing defect that severely reduces CFTR levels at the epithelial surface and also disrupts channel opening. The latter gating defect is also seen in other mutations, such as the G551D mutation. Lumacaftor and tezacaftor are both CFTR correctors, which improve trafficking of CFTR to the epithelial cell surface. Ivacaftor is a CFTR potentiator and acts by increasing the probability of the channel remaining open. Randomized controlled trials have proven that treatment with these compounds is associated with improved lung function in CF,66-69 and improvement of CF‐associated CRS following treatment with CFTR modulators has been reported anecdotally.70, 71 There is emerging evidence that CFTR dysfunction is a trait in other UADs and may be a target for treatment. CF carrier mutations are implicated in CRS patients who do not have CF.72 Constituents in tobacco smoke such as cadmium, arsenic, and acrolein can cause CFTR dysfunction,73 either by reducing CFTR expression or by inducing gating defects. CFTR decrements are also seen in COPD, including reduced nasal and lower airway potential difference74 and elevated sweat chloride,75 and the degree of CFTR impairment correlates with severity of symptoms and airflow limitation.74, 75 Ivacaftor reverses the acute reduction of CFTR activity after exposure to cigarette smoke in human bronchoepithelial cells,76 and has been demonstrated to ameliorate chronic bronchitis symptoms and improve CFTR activity in a preliminary study.77 Roflumilast, a phosphodiesterase‐4 inhibitor, can stimulate CFTR by increasing cyclic adenosine monophosphate and reverses smoke‐induced inhibition of CFTR activity.78 Roflumilast is approved for reducing exacerbations in severe COPD associated with chronic bronchitis. 3.2 Primary ciliary dyskinesia (PCD): bronchiectasis‐chronic rhinosinusitis due to ciliary dysfunction Chronic rhinosinusitis and bronchiectasis are universal in adults with PCD. The underlying pathophysiology is absent or impaired ciliary motility due to heterogeneous recessive mutations affecting the biogenesis of cilia lining the upper and lower airways.79 In turn, this leads to impaired mucociliary clearance manifesting in the neonatal period as difficulty feeding due to nasal blockage/rhinitis, neonatal respiratory distress syndrome and later in life as recurrent sinopulmonary infections, and bronchiectasis. Nasal nitric oxide is an excellent screening test for patients with a history suggestive of PCD.80 Other tests to assess for ciliary dyskinesia include analysis of ciliary ultrastructure by electron microscopy, assessment of ciliary beat frequency and pattern by high resolution, high‐speed video microscopy, and immunofluorescent staining of ciliary proteins. Ciliary dysfunction occurs in other airway diseases but is usually acquired, for example, due to smoking or infection. In CRS, blunted ciliary response to environmental stimuli has been demonstrated, and this is reversed once the tissue is removed from infected/inflamed environment.81 In COPD, cigarette smoke is associated with ciliary abnormalities in both bronchial82 and nasal mucosae.83 Sputum from atopic and non‐atopic asthmatics have ciliary inhibitory effect on human bronchoepithelial cell cultures, which was reversible upon removal of the sputum.84 Bronchial biopsies from asthma patients demonstrate reduced ciliary number which recovers after treatment with inhaled corticosteroids.85 There are currently no validated effective therapies for primary ciliary dyskinesia and this should be a focus for future research. In acquired cases, removal of the causative factor may reverse ciliary impairment. 3.3 Primary antibody deficiency The most common immunodeficiencies associated with CRS and bronchiectasis are primary antibody deficiencies,86 of which common variable immunodeficiency (CVID), characterized by reduced serum IgG concentrations, is the most common in adults. One‐third and two‐thirds of patients with CVID have bronchiectasis and recurrent sinusitis, respectively.87 Specific antibody deficiency, which is associated with normal immunoglobulin and IgG subclass levels but impaired antibody response to encapsulated respiratory pathogens such as Streptococcus pneumoniae and Hemophilus influenza, is also associated with a high prevalence of CRS and bronchiectasis, accounting for as many as 50% of idiopathic bronchiectasis.88 Patients with primary antibody deficiency most likely require lifelong immunoglobulin replacement, vaccinations, and prophylactic antibiotics. There is also some evidence that antibody deficiency may be a treatable underlying contributor in other airway diseases. For example, low circulating IgG levels are associated with higher rate of exacerbations and shorter time to next exacerbation in two COPD cohorts.89 Treatment with immunoglobulin replacement is associated with significant reduction in exacerbations and rescue antibiotic use in a small case series of 14 COPD patients (Supporting Information: References S8), warranting future prospective, randomized clinical trials to assess the efficacy of IVIG in preventing exacerbations in selected COPD patients with antibody deficiency. A potential contributing role of antibody deficiency in asthma has also been suggested by a small case‐control study which found that asthma patients are more likely to have a diagnosis of CVID or selective IgA deficiency than non‐asthmatic individuals, potentially accounting for the increased risk of bacterial infections in some individuals with asthma.90 A preliminary proof‐of‐concept study found that IVIG significantly reduces the frequency of asthma exacerbations and improved asthma control in adults with IgG subclass deficiency.91 4 EXOGENOUS COFACTORS The respiratory tract is continuously in contact with air from the environment which contains particulates such as microbes, pollutants, and other noxious agents that can cause or aggravate UAD. Aeroallergens such as house dust mites, pollen, and animal dander are the archetypal examples of how specific exposures can cause and worsen allergic asthma‐rhinitis. There are several other well‐delineated phenoendotypes of UAD in which specific inciting or aggravating cofactors are implicated. 4.1 Occupational asthma‐rhinitis More than 90% of individuals with occupational asthma (OA) also have occupational rhinitis (OR).92 Different occupational exposures can cause OA‐OR by different mechanisms. High molecular weight sensitizers, such as proteins and glycopeptides, often cause symptoms after a latency period via IgE‐mediated hypersensitivity.93 In contrast, the mechanism by which low molecular weight agents induces OA‐OR is poorly understood. Single or multiple exposures to high concentrations of irritants can lead to nonspecific inflammation in both upper and lower airways, clinically recognized as reactive upper airways dysfunction syndrome and reactive airways dysfunction syndrome, respectively. In addition to usual care for asthma and rhinitis, the management of OA‐OR is centered around exposure avoidance and use of appropriate respiratory protection equipment. The efficacy of omalizumab for sensitizing agents with IgE‐dependent reactions requires future studies. 4.2 Aspirin‐exacerbated respiratory disease The clinical phenotype of aspirin‐exacerbated respiratory disease (AERD) consists of a triad of asthma, CRSwNP, and exacerbation of upper and lower respiratory tract symptoms within 30 minutes to 3 hours after exposure to aspirin and other cyclooxygenase‐1‐inhibiting drugs. Nasal polyps in AERD can be distinguished from CRSwNP in individuals without AERD by the presence of enhanced eosinophilia, GM‐CSF, and decreased tissue plasminogen activator.94 The endotype of AERD is not fully understood but current available data suggest an underlying dysregulation of arachidonic acid metabolism, with constitutive overproduction of proinflammatory cysteinyl leukotrienes and decreased levels of anti‐inflammatory mediators such as prostaglandin E2.95 This dysregulation is aggravated by cyclooxygenase inhibition following exposure to aspirin and other non‐steroidal anti‐inflammatory drugs in susceptible individuals. The gold standard for diagnosing AERD is aspirin challenge, but challenge testing carries the risk of severe bronchospasm. Urinary leukotriene E4, the end‐product of arachidonic acid metabolism, is raised in AERD and may have a role in diagnosing AERD.96 Treatment options include avoidance of aspirin and NSAIDs, desensitization, and leukotriene receptor antagonists. Omalizumab and mepolizumab may be helpful in AERD as suggested by small trials involving subsets of patients with AERD (Supporting Information: References S9, S10). Whether the observed clinical efficacy of these biologics can be attributed to target AERD‐specific endotype above and beyond their effect on type‐2 eosinophilic inflammation is unclear. 4.3 Asthma‐CRS: hypersensitivity to Staphylococcus aureus enterotoxins Staphylococcus aureus is consistently found in nasal tissues of CRS patients, and evidence supports a role for S. aureus in the pathogenesis of CRS‐asthma. S. aureus colonizes nasal polyps and secretes proteins, including enterotoxins and serine protease‐like proteins in the nasal mucosa, which have the ability to elicit a polyclonal IgE response resulting in an intense type 2, IL‐5 high, eosinophilic inflammation which is likely responsible for chronic severe inflammation of the airways. Presence of sIgE to S. aureus enterotoxins in nasal polyp tissue is strongly associated with asthma in patients with CRSwNP,31, 97 providing an etiological link between asthma‐CRS. In a small placebo‐controlled, proof‐of‐concept study, omalizumab was found to ameliorate nasal polyps and airway symptoms in a small cohort of patients with asthma‐CRSwNP who demonstrated sIgE toward S. aureus enterotoxins.98 4.4 Allergic bronchopulmonary aspergillosis‐allergic aspergillus rhinosinusitis: fungal hypersensitivity IgE‐mediated hypersensitivity to Aspergillus hyphae is the underlying endotype for allergic bronchopulmonary aspergillosis (ABPA) and allergic aspergillus rhinosinusitis (AARS). Upper airway disease is characterized by pansinusitis, passage of nasal plugs, and recurrent nasal polyposis. Lower airway disease is characterized by mucus inspissation within the bronchi and severe asthma, central bronchiectasis, mucous plugging, and fleeting pulmonary infiltrates. In a case series, 22/95 patients of ABPA had also concomitant AARS. All these patients had positive skin tests, positive precipitins, and raised total and sIgE (Supporting Information: References S11). This combination of ABPA and AAS has been termed “sinobronchial allergic mycosis” to recognize their shared etiology and association. The optimal treatment of ABPA and AAS is not known but includes the use of steroids, antifungals, or omalizumab. 5 CONCLUSION The evidence for UAD is strongest for asthma and AR/CRS. However, close associations between upper airway diseases and other lower respiratory tract disorders can also be appreciated. UAD is complex and heterogeneous but a “treatable traits” paradigm, based on assessment of airway inflammation, mucosal defense dysfunction, and exogenous cofactors can help to identify pathophysiological mechanisms involved in the development of disease and potential targets for intervention in individuals presenting with combined upper and lower airway disease. A given individual with disease can demonstrate multiple traits which may vary over time. We have summarized the various treatable traits in UAD and their proven or notional targeted treatments in Table 2. Appreciation of these treatable traits is necessary toward advancing the precision medicine approach in UAD. CONFLICT OF INTEREST The authors declare that they have no conflicts of interest. Supporting Information REFERENCES Notes : AR, allergic rhinitis; CAT, COPD Assessment Tool; CRSsNP, chronic rhinosinusitis without nasal polyps; CRSwNP, chronic rhinosinusitis with nasal polyps; FEV1, forced expiratory volume in one second; ICS, inhaled corticosteroids; ICS + LABA, combination inhaled corticosteroids and long‐acting beta agonist; LABA, long‐acting beta agonist; LAMA, long‐acting muscarinic antagonist; mMRC, modified Medical Research Council dyspnea score. Typical upper and lower airway clinical phenotypes associated with underlying treatable traits are listed. Taxonomy based on clinical phenotypes has significant limitations: each phenotype may represent comprise treatable traits, for example, CRSwNP and asthma may be neutrophilic or eosinophilic inflammation depending on the population studied. Hence, a more precise approach is needed to identify contributory treatable trait(s) in each case, which can aid in selection of targeted treatments. Question mark (?) indicates targeted therapies under investigation. Treatable traits and targeted therapies may be used to complement the current approaches for patient stratification and treatment selection—including non‐targeted treatments—shown in Table 1. Citing Literature Number of times cited: 2 Ana Margarida Pereira, Cristina Jácome, Rute Almeida and João Almeida Fonseca, How the Smartphone Is Changing Allergy Diagnostics, Current Allergy and Asthma Reports, 10.1007/s11882-018-0824-4, 18, 12, (2018). Crossref Umut Can Kucuksezer, Cevdet Ozdemir, Mubeccel Akdis and Cezmi A. Akdis, Precision/Personalized Medicine in Allergic Diseases and Asthma, Archivum Immunologiae et Therapiae Experimentalis, 10.1007/s00005-018-0526-6, (2018). Crossref
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Acute lung injury is a neutrophil-dominant, life-threatening disease without effective therapies and better understanding of the pathophysiological mechanisms involved is an urgent need. Here we show that interleukin (IL)-22 is produced from innate lymphoid cells (ILC) and is responsible for...
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Research ArticleGastroenterologyInflammation Free access | 10.1172/jci.insight.121886 Essential role of IFN-γ in T cell–associated intestinal inflammation Yoshihiro Eriguchi,1 Kiminori Nakamura,2 Yuki Yokoi,2 Rina Sugimoto,2 Shuichiro Takahashi,3 Daigo Hashimoto,3 Takanori Teshima,3 Tokiyoshi Ayabe,2 Michael E. Selsted,1 and André J. Ouellette1 First published September 20, 2018 - More info Abstract Paneth cells contribute to small intestinal homeostasis by secreting antimicrobial peptides and constituting the intestinal stem cell (ISC) niche. Certain T cell–mediated enteropathies are characterized by extensive Paneth cell depletion coincident with mucosal destruction and dysbiosis. In this study, mechanisms of intestinal crypt injury have been investigated by characterizing responses of mouse intestinal organoids (enteroids) in coculture with mouse T lymphocytes. Activated T cells induced enteroid damage, reduced Paneth cell and Lgr5+ ISC mRNA levels, and induced Paneth cell death through a caspase-3/7–dependent mechanism. IFN-γ mediated these effects, because IFN-γ receptor–null enteroids were unaffected by activated T cells. In mice, administration of IFN-γ induced enteropathy with crypt hyperplasia, villus shortening, Paneth cell depletion, and modified ISC marker expression. IFN-γ exacerbated radiation enteritis, which was ameliorated by treatment with a selective JAK1/2 inhibitor. Thus, IFN-γ induced Paneth cell death and impaired regeneration of small intestinal epithelium in vivo, suggesting that IFN-γ may be a useful target for treating defective mucosal regeneration in enteric inflammation. Graphical Abstract Introduction Paneth cells of the small intestinal epithelium contribute to small bowel homeostasis (1). First, they secrete α-defensins (2), which both confer immunity to Salmonella enterica serovar Typhimurium infection (3) and select the composition of the ileal microbiota (4–6). Also, they contribute to crypt stability by releasing niche signals for maintenance of Lgr5+ crypt intestinal stem cells (ISCs), which position themselves to optimize surface contact with Paneth cells (7), and Paneth cells stimulate ISC numbers to expand during caloric restriction via mTORC1 signaling (8). Thus, physiologic events that impair Paneth cell health and viability jeopardize enteric homeostasis, representing risk factors associated with inflammatory bowel diseases. Paneth cell homeostasis is sensitive to proinflammatory conditions that induce Paneth cell depletion and may impair the ability of crypt ISCs to proliferate and regenerate the epithelial barrier. For example, loss of Paneth cells is associated with the onset of inflammation in graft-versus-host disease (GVHD) (9–11), during Toxoplasma gondii infection (12, 13), and in autoimmune enteropathy (AIE) (14–17). The subsequent reductions in mucosal defense mechanisms and the resulting dysbiosis exacerbate inflammation and may compromise tissue repair by disturbing the ISC crypt microenvironment. In GVHD, loss of Paneth cells is associated with gut dysbiosis and bacterial translocation across the epithelial barrier (9, 10), which positively correlates with mortality (9–11). Similarly, in mice infected with T. gondii, activated CD4+ Th1 cells and intestinal dysbiosis both induce transient, IFN-γ–dependent elimination of Paneth cells (12, 13). Immune responses to the parasite are complex, in that germ-free mice do not develop intestinal pathology during T. gondii infection (12). The microbiota activated Paneth cell–specific autophagy via induction of IFN-γ, and deletion of Atg5 in Paneth cells exacerbated intestinal immunopathology in response to T. gondii infection (13). In ex vivo studies investigating Paneth cell degranulation, IFN-γ was identified as mediating release of host defense molecules into the lumen of cultured enteroids (18). Enteroids, small intestinal crypt organoids, consist of a 3D epithelial monolayer that maintains crypt-villus architecture with replicating ISCs that differentiate into the major small intestinal epithelial lineages (19). Exposure of enteroids to IFN-γ induced Paneth cells to extrude their secretory granules and nuclei. Also, IFN-γ increased the number of enteroid cells positive for cleaved caspase-3, although FACS analyses did not identify which cells were positive for activated caspase (18). In addition, exposure of enteroids to IFN-γ reduced Paneth cell and ISC marker expression, and induced MHC class II expression in all enteroid cells (18), suggesting that IFN-γ exerts direct adverse effects on all intestinal epithelial populations. To improve understanding of effector mechanisms that mediate crypt injury by activated T cells, we investigated mouse enteroids in coculture with activated T cells to identify mediators of inflammation-induced Paneth cell loss. Using this ex vivo system, we identified proinflammatory mediators released by activated T cells and characterized enteroid responses to specific cytokines, demonstrating that IFN-γ targets Paneth cells and Lgr5+ ISCs. Subsequently, we showed that systemic administration of IFN-γ to mice disturbed ileal crypt homeostasis in vivo, and crypts depleted of Paneth cells by IFN-γ were highly sensitive to injury by sublethal irradiation and failed to recover. Results Activated T cells induce enteroid damage associated with Paneth cell and Lgr5+ ISC loss ex vivo. Because activated donor T cells are primarily responsible for GVHD etiology (9, 10), and parasite-induced Th1 cells are associated with Paneth cell elimination (12), we tested whether activated T cells secrete factors that disrupt the intestinal epithelium. Studying mouse enteroids cultured ex vivo allowed epithelial responses to T cell activation to be isolated from possible humoral or paracrine factors released by gut stromal cells, distal tissues, or the gut microbiota. Activation of mouse splenic CD4+ or CD8+ T cells with anti-CD3/28 in coculture with enteroids (Figure 1, A and B) induced enteroid damage within 2 days, with increasing severity over 3–4 days (Figure 1, B–E); but in the absence of T cells, anti-CD3/28 had no effect on enteroid integrity (data not shown). The lack of damage in cocultures with resting T cells demonstrated the requirement for T cell activation (Figure 1, B, D, and E). Figure 1 Activated T cells induce enteroid damage. (A) Overall design of enteroid and T cell coculture experiments. (B) Enteroids cocultured with CD4+ or CD8+ T cells (5 × 104 cells per well) with (activated) or without (resting) anti-CD3/anti-CD28 beads. (C) Enteroid damage scoring system. Damage scores of enteroids cocultured with CD4+ (D) or CD8+ (E) T cells. Data are representative of 2 independent experiments and are shown as mean ± SEM (n = 100 enteroids per group); gray bars, enteroids alone; blue bars, enteroids plus resting T cells; red bars, enteroids plus activated T cells. Dunnett’s multiple comparisons test was used to compare each group with the control group. ***P < 0.001. Scale bars: 200 μm. Because the number of recognizable Paneth cells is reduced in GVHD (9) and T. gondii infection (12), lineage-specific marker mRNAs in enteroids incubated with activated or resting T cells were quantified to test for selective reductions in Paneth cells and Lgr5+ ISCs. Quantitative reverse transcription PCR (qRT-PCR) analyses showed that levels of Paneth cell α-defensin-22 (Defa22) and ISC Lgr5 mRNAs were reduced in enteroids incubated for 1–2 days with activated but not resting T cells (Figure 2, A–D). Enteroids embedded in Matrigel did not contact T cells directly (Figure 1B), suggesting that soluble factors released by activated T cells affected Paneth cell and ISC marker mRNA expression. Exposure to activated CD8+ T cells caused a greater reduction in Paneth cell and ISC marker mRNA levels than did CD4+ T cells, implying that CD8+ T cells release higher levels of, or additional, enteroid-damaging factors. Figure 2 Activated T cells reduce Paneth cell and Lgr5+ ISC marker mRNA levels. (A–D) Enteroids cocultured with CD4+ or CD8+ T cells (5 × 104 cells per well) with (activated) or without (resting) anti-CD3/anti-CD28 beads. After removal of CD4+ (A and C) and CD8+ (B and D) T cells, enteroid RNAs were analyzed by qRT-PCR to measure levels of Defa22 (A and B) and Lgr5 (C and D) mRNAs. Data are representative of 2 independent experiments and shown as mean ± SEM (enteroids alone, n = 3 independent wells, gray bars; enteroids + resting T cells, n = 4, blue bars; enteroids + activated T cells, n = 4, red bars). Dunnett’s multiple comparisons test was used to compare each group with the control group. *P < 0.05, **P < 0.01, ***P < 0.001. IFN-γ induces enteroid damage and Paneth cell and Lgr5+ ISC loss. To identify T cell mediators of enteroid damage, ELISAs were performed to measure cytokines in mixed culture media from 1 to 4 days after T cell activation. Levels of IFN-γ, TNF-α, IL-2, and IL-17A secreted by activated CD4+ and CD8+ T cells increased relative to unactivated T cells (Supplemental Figure 1, A–J; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.121886DS1). Only low levels of IL-6 secretion were detected, and none of the cytokines were released by unactivated T cells. Accordingly, enteroids exposed to secreted cytokines at the highest levels detected (Supplemental Figure 1, A–J) were evaluated for loss of integrity. At 2 ng/ml, IFN-γ damaged enteroids within 2 days, but no other cytokine tested affected enteroid integrity (Figure 3, A and B). The effects of IFN-γ on enteroid epithelial lineages were tested by quantifying lineage marker mRNAs, including Defa22 (Paneth cells), Lgr5 (rapidly cycling ISCs), Bmi1 (quiescent ISCs), Muc2 (goblet cells), Dclk1 (tuft cells), Chga (enteroendocrine cells), and Alpi (enterocytes) in enteroids treated with IFN-γ for 3 days. Relative to control enteroids not exposed to cytokines, IFN-γ reduced Defa22 mRNA 450-fold and Lgr5 mRNA 24-fold (Figure 3C), but effects of IFN-γ on Dclk1, Muc2, and Chga mRNAs were modest, and Bmi1 and Alpi mRNA levels were not affected significantly (Figure 3C). All lineage marker mRNAs remained at normal levels in enteroids exposed to all other cytokines tested (Figure 3C). Figure 3 IFN-γ induces enteroid damage. (A) Enteroids were exposed to IFN-γ, TNF-α, IL-2, and IL-17A, the highest levels released into coculture media, or with 100 pg/ml in the case of IL-6 to determine which cytokine(s) mediate enteroid damage. Only IFN-γ treatment caused damage. (B) Damage scores of enteroids exposed for 3 days to the proinflammatory cytokines shown. Data are from 2 independent experiments and shown as mean ± SEM (n = 100 enteroids per group). (C) qRT-PCR analyses of lineage markers in enteroids exposed to cytokines for 3 days. Data are representative of 2 independent experiments and shown as mean ± SEM (n = 4 independent wells). Dunnett’s multiple comparisons test was used to compare each group with the control group. *P < 0.05, **P < 0.01, ***P < 0.001. Scale bar: 200 μm. IFN-γ induces dose-dependent loss of Paneth cells and rapidly cycling ISCs. To assess the relative contribution of activated CD4+ and CD8+ T cell–derived IFN-γ to the induction of Paneth cell and Lgr5+ ISC loss, enteroids were cultured for 3 days with IFN-γ at levels released by both activated T cell populations. At 500 pg/ml, the maximum level of IFN-γ released by CD4+ T cells (Supplemental Figure 1A), enteroid damage was extensive (Figure 4), and mRNA levels for Paneth cell markers Defa22, Defa5, pan-cryptdins, and lysozyme were reduced significantly by IFN-γ in a dose-dependent manner (Figure 5A and Supplemental Figure 2, A–C). Also, levels of Lgr5 and Olfm4 mRNAs, markers of rapidly cycling ISCs downstream of Wnt and Notch signaling (20, 21), decreased (Figure 5, C and D), as did mRNAs for Paneth cell niche factors Wnt3 and Notch ligand Dll4 (Figure 5, E and F). Bmi1 mRNA levels were similar to controls (Figure 5B), as were mRNAs that mark the other major epithelial lineages (Supplemental Figure 2, D–G). We conclude that the quantity of IFN-γ secreted by CD4+ T cells is sufficient to induce loss of enteroid integrity, but CD8+ cell activation is judged to have a greater impact on enteroid Paneth cells and Lgr5+ ISCs, because they release 4 times more IFN-γ than CD4+ T cells. Figure 4 IFN-γ induces dose-dependent enteroid damage. Enteroids were exposed to IFN-γ for 3 days as shown. Representative images from 2 experiments are shown. Scale bar: 200 μm. Figure 5 IFN-γ induces dose-dependent loss of Paneth cells and rapidly cycling stem cells. Enteroids were exposed to IFN-γ for 3 days. (A–G) qRT-PCR analyses to quantify lineage-specific mRNAs, niche signal mRNAs of Paneth cell origin, and apoptosis mRNA levels in enteroids exposed to IFN-γ for 1, 2, and 3 days. Data are from 2 independent experiments and are shown as mean ± SEM (n = 4 independent wells). Dunnett’s multiple comparisons test was used to compare each group with the control group at each time point. *P < 0.05, **P < 0.01, ***P < 0.001. IFN-γ induces Paneth cell death through a caspase-3/7–dependent pathway. In a previous study, the overall fraction of enteroid cells positive for cleaved caspase-3 increased with IFN-γ exposure, although the identities of the positive cells were not reported (18). To identify enteroid cells that have apoptotic responses to IFN-γ exposure (18), we tested whether IFN-γ specifically induces Paneth cell death by quantifying Casp3 mRNA. Over 3 days, IFN-γ increased enteroid Casp3 mRNA dose-dependently (Figure 5G), and its sustained expression contrasted with the reduced levels of Paneth cell marker mRNAs (Figure 5A), suggesting that IFN-γ was inducing Casp3-dependent Paneth cell death. To test for cleaved caspase-3 in Paneth cells, caspase-3/7 activity was visualized by live confocal microscopy of enteroids exposed to 2 ng/ml IFN-γ (Figure 6 and Supplemental Videos 1 and 2), which showed that caspase-3/7 activation occurred in Paneth cells within 13–16 hours of cytokine exposure (Figure 6 and Supplemental Videos 1 and 2). Concurrent with caspase-3/7 activation, Paneth cells extruded their cell contents into the crypt lumen, as previously reported (18). We conclude that reduction of Paneth cell marker mRNAs by IFN-γ occurs by selective induction of cell death by caspase-3/7 activation. Figure 6 IFN-γ induces Paneth cell death through a caspase-3/7–dependent pathway. Still images from time-lapse analysis of caspase-3/7 activity in an enteroid exposed to IFN-γ (from Supplemental Videos 1 and 2). Paneth cells (white arrowheads) are granule-containing and appear white in the differential interference contrast images (top row). Cells containing activated caspase-3/7 have bright green nuclei (red arrowheads), which were detected only in Paneth cells and extruded into the crypt lumen after caspase-3/7 activation (bottom row). Time after addition of 2 ng/ml IFN-γ is indicated in the upper left corner of each image. Representative images from 2 experiments are shown. Scale bars: 20 μm. IFN-γ is required for induction of enteroid damage by activated splenocytes. To test whether Paneth cell and ISC depletion depended exclusively on IFN-γ, we measured IFN-γ receptor–null (IFN-γRKO) enteroid responses to coculture with activated splenic T cells. As before (Figure 1B), activated splenocytes from C57BL/6 (WT) mice induced damage in WT enteroids within 2–4 days, but IFN-γRKO enteroids grew and differentiated normally under the same coculture conditions (Figure 7, A and B). WT enteroids cocultured with activated T cells for 4 days had markedly reduced levels of Paneth cell Defa22 and ISC Lgr5 mRNAs. In contrast, Defa22 mRNA levels remained normal, and Lgr5 mRNA was only slightly lower in IFN-γRKO enteroids under the same conditions (Figure 7C). Whether the 2- to 4-fold changes in other lineage markers are meaningful relative to the magnitude of effects on WT Paneth cells and Lgr5+ ISCs is unclear (Figure 7C). The moderate reduction in the ISC, enteroendocrine cell, and enterocyte markers in cocultured IFN-γRKO enteroids (Figure 7C) suggests that cytokines other than IFN-γ from activated T cells also may induce damage, but to a lesser extent. Activated T cells increased Casp3 mRNA ~6-fold in WT enteroids but not in IFN-γR knockouts (Figure 7C). We conclude that IFN-γ signaling mediates selective Paneth cell and Lgr5+ ISC depletion under induced proinflammatory conditions. Figure 7 IFN-γ mediates enteroid damage induced by splenocyte activation. (A) WT or IFN-γ receptor–KO (IFN-γRKO, KO) enteroids in coculture with WT splenocytes with or without activation using anti-CD3/anti-CD28 beads. (B) Damage scores of WT or KO enteroids in coculture with control or activated WT splenocytes. Data are representative of 2 independent experiments and shown as mean ± SEM, with n = 100 enteroids per group. (C) qRT-PCR analyses to quantify lineage-specific and apoptosis marker mRNAs in WT or IFN-γRKO enteroids in coculture with control or activated WT splenocytes for 4 days. Data are representative of 2 independent experiments and shown as mean ± SEM (n = 5 independent wells). Dunnett’s multiple comparisons test was used to compare each group with the WT control group. *P < 0.05, **P < 0.01, ***P < 0.001. Scale bar: 200 μm. IFN-γ receptor 1 expression on both Paneth cells and Lgr5+ ISCs. To test for the lineage-specific expression of the IFN-γ receptor, single-cell suspensions of CD24hiLgr5-EGFPlo Paneth cells and Lgr5-EGFPhi ISCs isolated from Lgr5-GFP-CreERT2 mouse small intestinal crypts were analyzed via flow cytometry for IFN-γ receptor 1 (Ifngr1) expression (Supplemental Figure 3, A–D). The data show that Paneth cell and Lgr5+ ISC levels of Ifngr1 were equivalent (Supplemental Figure 3, E and F), and a priori both crypt subpopulations appear to be equally capable of responding to IFN-γ. Accordingly, determining whether IFN-γ exerts direct or indirect effects on Paneth cells or Lgr5+ ISCs will require analyses of lineage-specific conditional knockouts. Ruxolitinib prevents IFN-γ–induced enteroid damage. To test whether the effects of IFN-γ could be prevented with targeted therapy, WT enteroids treated with IFN-γ were cultured with 0.1–10 μM ruxolitinib, a selective inhibitor of JAK1/2 in IFN-γ signaling (22). Ruxolitinib inhibited IFN-γ signaling in enteroids, as confirmed by suppression of Socs1 gene expression (Supplemental Figure 4C), and it diminished IFN-γ–induced enteroid damage dose-dependently without affecting enteroid integrity, growth, or differentiation (Supplemental Figure 4, A and B). Ruxolitinib blocked IFN-γ–induced Casp3 expression (Supplemental Figure 4D) and prevented reductions in Defa22, Lgr5, and Olfm4 mRNAs, which remained at normal levels (Supplemental Figure 4, E, G, and H). Ruxolitinib did not alter enteroid Bmi1 mRNA levels regardless of IFN-γ challenge (Supplemental Figure 4F). Thus, IFN-γ induces selective effects on Paneth cells and ISCs in enteroids that are prevented by ruxolitinib. Exogenous IFN-γ depletes Paneth cells and disrupts the ileal crypt niche in mice. IFN-γ released by activated T cells disrupts enteroid integrity and crypt homeostasis by selective reduction of Paneth cells and Lgr5+ ISCs, and T cell activation also induces IFN-γ–dependent Paneth cell loss in vivo (12, 18). The effects of IFN-γ on rapidly cycling ISCs in vivo were tested by i.p. administration to mice, followed by immunofluorescence and histochemical staining of terminal ileal samples (Figure 8A). Paneth cell numbers and levels of the Paneth cell α-defensin Defa1 (cryptdin-1) were reduced in ileum by IFN-γ treatment (Figure 8, C, F, and I, and Figure 9E), and crypts that were positive for Lgr5 and Olfm4 decreased with exogenous IFN-γ administration (Figure 9, F and G). Although IFN-γ reduced Olfm4 staining in ileal crypts (Figure 8I), diffuse Lgr5 immunofluorescence still was detected in crypts that lacked apparent Paneth cells (Figure 8F). These findings suggest that exogenous IFN-γ resulted in replacement of Lgr5+ and Olfm4+ rapidly cycling ISCs with Lgr5lo and Olfm4–negative (Lgr5loOlfm4–) cells in association with apparent loss of Paneth cells. In vivo IFN-γ treatment reduced ileal Defa22 mRNA ~300-fold and Olfm4 mRNA ~30-fold, but Lgr5 mRNA levels were nearly normal in ileum (Figure 9H), consistent with the immunohistological findings (Figure 8F). Exogenous IFN-γ modified ileal morphology, inducing villus shortening and crypt elongation (Figure 8C and Figure 10B). These defects resemble a phenotype common in GVHD (9), T. gondii infection (12), and AIE (14–16, 23), suggesting that IFN-γ contributes to disease pathogenesis. Compared with the ~300-fold reduction in ileal Defa22 mRNA, IFN-γ treatment had modest effects on other ileal lineage markers (Figure 9H), except for enterocyte Alpi mRNA, which was reduced as a possible consequence of the shortened ileal villi (Figure 8C). As in enteroids, inhibition of IFN-γ signaling by ruxolitinib in vivo protected Paneth cells and rapidly cycling ISCs in ileum (Figure 8, D, G, and J, and Figure 9, E–H). Thus, exogenous IFN-γ caused ileal Paneth cell depletion, with Lgr5loOlfm4– cell replacement of Lgr5+Olfm4+ ISCs (Figure 8, F and I) and disruption of normal crypt-villus architecture (Figure 8C and Figure 10B). These findings demonstrate that exogenous IFN-γ alters the ileal niche in vivo in a manner resembling enteroid exposure to IFN-γ ex vivo. Figure 8 Exogenous IFN-γ depletes Paneth cells and modifies the expression of rapidly cycling ISC markers in vivo. (A) Overall experimental scheme for IFN-γ and ruxolitinib administration in mice. Ileum samples were collected 72 hours after the first dose of IFN-γ. Histochemical staining (H&E) of ileum sections from control (B), IFN-γ–treated (C), or IFN-γ + ruxolitinib–treated (D) C57BL/6 mice. (E–J) Confocal image for cryptdin-1 (red) of Lgr5-EGFP-ires-creERT2 mouse ileum sections. (E–G) Lgr5-GFP+ ISCs are green (white arrows). (H–J) Sections stained for Olfm4 (green) with DAPI (blue). Control (E and H), IFN-γ–treated (F and I), and IFN-γ + ruxolitinib–treated (G and J) ileum sections are shown. The results are representative of 2 experiments. Note that some ileal crypts of IFN-γ–treated mice lack Paneth cells and Olfm4+ ISCs (I), but crypts that are faintly positive for Lgr5-GFP cells are still evident (F). Scale bars: 100 μm. Figure 9 Aggravated radiation enteropathy and impaired epithelial regeneration induced by IFN-γ. (A) Schematics of the study to determine effects of TBI, IFN-γ, and ruxolitinib on intestinal epithelium in mice. Ileum tissue was collected 48 hours after TBI and analyzed. (B) Representative small intestines of control (C), IFN-γ (I), IFN-γ + ruxolitinib (IR), TBI (T), TBI + IFN-γ (TI), and TBI + IFN-γ + ruxolitinib (TIR) mice are shown. Scale bars: 8 cm. (C) Lengths of small bowels in cohort. Measurements from 2 experiments were combined and presented as mean ± SD; control group, n = 4; TIR, n = 7; remaining groups, n = 6. (D–G) Quantification of crypt numbers per ileum circumference section at 48 hours after TBI. Whole (D), cryptdin-1+ (E), Lgr5-GFP+ (F), and Olfm4+ (G) crypts were counted in 2 ileum circumference sections of 3 different Lgr5-EGFP-ires-creERT2 mice from each group. Data are from 2 separate experiments and show mean ± SD. (H and I) qRT-PCR analyses were performed to quantify mRNAs coding for lineage-specific markers, niche factors, and requisite lineage-determining transcription factors in whole terminal ileum tissue. Data from 2 separate experiments were combined and are shown as mean ± SEM; TIR group, n = 7; all other groups, n = 6 biological replicates. Tukey’s multiple comparisons test was used to compare each cohort. Mean values of data in C–G and statistical results in C–I are presented in Supplemental Tables 2–4. Figure 10 IFN-γ modulation of ileal crypt cell proliferation in response to irradiation injury. (A) Schematics of the study to determine effects of TBI, IFN-γ, and ruxolitinib on intestinal epithelium in mice. Ileum tissue was collected 48 hours after TBI and analyzed. (B) IHC staining of Ki-67 in mouse ileal sections. Control (C), IFN-γ (I), IFN-γ + ruxolitinib (IR), TBI (T), TBI + IFN-γ (TI), and TBI + IFN-γ + ruxolitinib (TIR) are shown. Scale bars: 100 μm. (C) Ki-67+ cell numbers per longitudinal crypt section were counted in 30 ileal crypts per mouse. Data from 5 different C57BL/6 mice in each group were combined from 2 separate experiments and are shown as mean ± SD. Tukey’s multiple comparisons test was used to compare the each cohort. Statistical results of data in C are presented in Supplemental Table 5. IFN-γ increases intestinal radiosensitivity and associated mortality. Because IFN-γ disrupted rapidly cycling ISCs in vivo (Figure 8, C, F, and I), we tested its effects on the regenerative response to radiation injury. Mice that received IFN-γ were subjected to sublethal total body irradiation (TBI), followed by reconstitution with syngeneic bone marrow cells 24 hours after IFN-γ administration (Figure 11A). All TBI mice treated with IFN-γ (TI) developed profuse diarrhea beginning 32 hours after TBI and died within 2 days. In contrast, cohorts treated only with IFN-γ (I), receiving only TBI (T), or TI mice receiving ruxolitinib (TIR) did not develop diarrhea, recovered from body weight loss and clinical manifestations within 7 days of TBI, and all survived (Figure 11, B–D). Figure 11 IFN-γ increases the radiosensitivity of intestinal epithelial tissue. (A) Schematic depiction of TBI, and IFN-γ and ruxolitinib administration in mice. After TBI, mice received syngeneic bone marrow transplantation (BMT) to rescue from bone marrow death on day 0. Survival (B), body weight as a percentage of initial weight (C), and clinical severity scores (D) from 2 independent experiments were combined, and data are shown as mean values ± SEM (IFN-γ alone group, n = 6; TBI alone group, n = 6; TBI + IFN-γ group, n = 10; TBI + IFN-γ + ruxolitinib group, n= 10). (E–M) Histology of mouse ileal sections 48 hours after TBI. H&E staining of ileum sections from mice receiving TBI (E), TBI + IFN-γ (F), or TBI + IFN-γ + ruxolitinib (G). (H–M) Confocal imaging of Lgr5-EGFP-ires-creERT2 mouse ileum sections. Immunofluorescence staining of cryptdin-1 (red, H-M), Lgr5-GFP+ (green, white arrows, H-J), Olfm4 (green) and DAPI (blue) (K-M) for mice that received TBI (H and K), TBI + IFN-γ (I and L), or TBI + IFN-γ + ruxolitinib (J and M). The results are representative of 2 separate experiments and illustrate the reduction in crypt numbers and the loss and absence of Paneth cells and rapidly cycling ISCs in ileum of TBI + IFN-γ–treated mice (F, I, and L). Scale bars: 100 μm. To evaluate the combined effects of IFN-γ and irradiation on ileal homeostasis and pathology, we collected full-length intestines from T, TI, and TIR mice 2 days after TBI; from I mice and mice treated with IFN-γ + ruxolitinib without TBI (IR); and from control cohorts (C), which received only vehicle (Figure 9, A and B). In TI mice, the small intestinal lumen contained watery fluid (Figure 9B), and the intestine had contracted significantly in length compared with all cohorts except I mice (Figure 9, B and C, and Supplemental Tables 2 and 3). The terminal ilea of TI mice were depleted of Paneth cells and had disrupted crypt-villus architecture, with thinning of the epithelial lining (Figure 11F). TI induced differential effects on expression of ISC markers. For example, TI ileal Olfm4 mRNA was markedly reduced relative to control ileum, but Lgr5 mRNA levels were only ~3-fold lower (Figure 9H). The modest effects on Lgr5 mRNA levels appear to be inconsistent with the severity of crypt-villus destruction and the reduced numbers of Lgr5+ crypts in TI ileum (Figure 9F and Figure 11, F and I). Their weak and diffuse immune staining suggested that Lgr5+ ISCs had been depleted. Also, Olfm4 and Defa1 staining both were diminished (Figure 9, E and G, and Figure 11, I and L), and, as observed in I mice, TI reduced ileal Defa22 mRNA levels markedly (Figure 9H). To evaluate ileal disruption further, crypts in ileal cross sections were counted, which showed that IFN-γ reduced the number of crypts per circumference to 83% of the number in control ileum, and TI further reduced the number to 65% of control values (Figure 9D and Supplemental Tables 2 and 3). Thus, the loss of Paneth cells and Lgr5+Olfm4+ ISCs induced by TI appears to impair epithelial regeneration secondary to depletion of functional rapidly cycling ISCs. Consequently, the total number of functioning crypts decreased with concomitant bowel shortening. Consistent with villus shortening and crypt loss (Figure 11F), TI also reduced enterocyte and goblet cell numbers, as evidenced by the respective ~450-fold and 26-fold decreases in Alpi and Muc2 mRNAs (Figure 9H). Reductions in Defa22 and Paneth cell niche factor mRNA levels in TI and I cohorts were not significantly different (Figure 9, H and I), showing that the additive effects of irradiation on Paneth cells in IFN-γ–treated mice were modest. Similarly, levels of mRNAs marking other ileal epithelial lineages were not significantly different between the TI and I groups (Figure 9H). As observed in enteroids (Supplemental Figure 4) and in ileum of IFN-γ–treated mice (Figure 8, D, G, and J, and Figure 9, E–H), ruxolitinib partially prevented the loss of ileal Paneth cells and rapidly cycling ISCs of TI mice, as well as IFN-γ–induced alterations to the crypt niche environment and differentiation factors (Figure 9, E–I, and Figure 11, G, J, and M). Also, ruxolitinib restored the number of crypts per ileum cross section, reduced contraction of the intestine (Figure 9, B–D), and conferred 100% survival on TIR mice (Figure 11B). Thus, ruxolitinib treatment may restore homeostasis from intestinal inflammation secondary to Paneth cell depletion mediated by IFN-γ. IFN-γ modulation of ileal crypt cell proliferation in response to irradiation injury. To assess the combined effects of IFN-γ and irradiation on the proliferation status of cells in ileal crypts, the number and distribution of Ki-67+ cells were quantified on a per-crypt basis. With IFN-γ administration, the number of crypt Ki-67+ cells increased, and crypt Ki-67+ cells became abundant at the crypt base in place of Ki-67– Paneth cells and slender Ki-67+ rapidly cycling cells (Figure 10, B and C). In contrast, in irradiated mice, IFN-γ reduced Ki-67+ crypt cell numbers and increased radiosensitivity (Figure 10, B and C). These data are consistent with disruption of rapidly cycling ISCs in vivo by IFN-γ, although whether IFN-γ effects are mediated directly or indirectly by the Paneth cell niche remains unknown. Ruxolitinib ameliorated the effect of IFN-γ on crypt cell proliferation regardless of irradiation injury (Figure 10, B and C). Discussion We have investigated molecular mechanisms by which activated CD4+ and CD8+ T cells mediate small intestinal injury. These studies were prompted, in part, by prior findings that GVHD is mediated by activated donor T cells after allogeneic hematopoietic stem cell transplantation in which Paneth cells are primary targets, and their loss correlates positively with GVHD mortality (9–11). In mouse crypt enteroids cocultured with activated T cells, IFN-γ from activated T cells mediated loss of epithelial enteroid integrity and induced Paneth cell loss via caspase-3/7 activation. In addition, IFN-γRKO enteroids were unresponsive to activated splenic T cells, demonstrating that IFN-γ was the soluble mediator of Paneth cell and rapidly cycling ISC loss. The rescue of enteroid integrity and prevention of Paneth cell death by ruxolitinib further confirmed the role of IFN-γ in targeting the intestinal epithelium. Because Paneth cells and Lgr5+ ISCs both express Ifngr1 (Supplemental Figure 3), whether IFN-γ acted directly or indirectly on Paneth cells and Lgr5+ ISCs remains unknown. Recently, the gut microbiota was shown to activate Paneth cell–specific autophagy by inducing IFN-γ, and the Paneth cell–restricted deficiency in autophagy led to intestinal pathology mediated by TNF-α and IFN-γ (13), providing insight into the basis of Paneth cell sensitivity to IFN-γ. To test whether enteroid responses to IFN-γ predict its effects in vivo, we administered IFN-γ systemically and determined its consequences on mouse ileum integrity and on recovery of mice from irradiation injury. Consistent with ex vivo findings, i.p. administration of IFN-γ in vivo depleted ileal Paneth cells, impaired recovery, and exacerbated morbidity and mortality in radiation-induced enteritis. IFN-γ greatly reduced expression of the rapidly cycling ISC marker Olfm4 but had only a negligible effect on Lgr5 expression in ileum (Figure 9H). In vivo in Atoh1-null mice, crypts are Paneth cell deficient but still maintain normal crypt architecture and Lgr5+ ISC function (24, 25). Ex vivo, however, Atoh1-null crypts fail to grow and cannot differentiate into enteroids without Wnt supplementation (24). Furthermore, Wnt3 is not required in vivo for maintenance of ISCs in mice, but crypt organoids in culture require Paneth cell–derived Wnt3 in order to develop (20). These findings imply that a Wnt source other than epithelial cells exists in vivo, perhaps deriving from stromal telocytes (26–28). Accordingly, the persistence of Lgr5 expression and its modified distribution pattern in ileum after IFN-γ administration (Figure 8, F and I) may be due to alternative Wnt signals from mesenchymal stromal cells following induced Paneth cell loss. Although IFN-γ–treated mice survived without TBI exposure, IFN-γ administration enhanced sensitivity to sublethal irradiation injury (Figure 11, B–D). The ileal pathology observed in mice after IFN-γ administration is consistent with reported IFN-γ–induced enteropathy with crypt hyperplasia (29). The results suggest that depletion of Paneth cells removes niche factors that they contribute normally to the crypt environment (30), perhaps inducing conversion of Lgr5+ ISCs to the transit-amplifying (TA) cell compartment, where Lgr5+Olfm4+ ISCs may differentiate or be replaced by Lgr5loOlfm4– cells. IFN-γ administration resulted in loss of Ki-67– Paneth cells from the crypt base and replacement with Ki-67+ rapidly cycling cells and increased numbers of Ki-67+ cells in crypts, possibly contributing to crypt hyperplasia (Figure 8, C and F, Figure 10, and Figure 12). We speculate that the restructured crypt cell subpopulations may be deficient in responding to irradiation-induced injury (Figure 11), perhaps because quiescent ISCs cannot differentiate into adequate numbers of functional rapidly cycling ISCs and TA cells that were depleted by radiation injury (Figure 10, B and C, and Figure 12). Of potential clinical relevance, patients with chronic inflammation and elevated levels of IFN-γ may have increased risk of enteropathy after abdominal irradiation or systemic chemotherapy. Figure 12 Schematic representation of hypothetical IFN-γ etiology augmenting irradiation injury. Upper images depict the course of crypt recovery from irradiation injury. Rapidly cycling ISCs that converted from quiescent ISCs after irradiation (center image, blue arrows) restore damaged crypts promptly (33, 34). Lower panel shows the hypothetical IFN-γ etiology. In the absence of niche signals previously derived from Paneth cells, Lgr5loOlfm4– cells, and TA cells become prevalent, and Lgr5loOlfm4– cells replace positions the base of the crypts that formerly were occupied by the depleted Paneth cells. The increase in Lgr5loOlfm4– cells relative to Lgr5+Olfm4+ ISCs may contribute to crypt hyperplasia. However, in crypts depleted of Paneth cells by IFN-γ exposure, Bmi1+ quiescent ISCs cannot convert to rapidly cycling ISCs in sufficient numbers to respond to irradiation, resulting in failure to repair and restore epithelial integrity. Blue arrows indicate ISC division. Our findings suggest that ruxolitinib may be a candidate for treating IFN-γ–induced Paneth cell loss. In the severe and prolonged inflammation of GVHD (9–11) driven by IFN-γ from activated T cells, the clinical outcome is made worse by systemic infections coincident with Paneth cell loss, dysbiosis, and lipopolysaccharide translocation across the damaged gut barrier. Those conditions stimulate donor T cells further and accelerate disease (9), which ruxolitinib ameliorates by increasing regulatory T cell numbers (31) and altering T cell trafficking (22) in GVHD mice. Also, in 2 patients with corticosteroid-refractory intestinal GVHD, ruxolitinib treatment reduced disease severity (31) and resulted in improvement of gut GVHD. We have focused in this report on direct adverse effects on small intestinal epithelial lineages and ISCs mediated by IFN-γ. The efficacy of ruxolitinib in preventing IFN-γ–induced effects and damage both ex vivo and in vivo identifies Paneth cells and the epithelium as potentially new cell targets for this therapeutic agent. Methods Mice. Female C57BL/6, B6.1297S7-Ifngr1tm1.Agt/J, and Lgr5-EGFP-ires-creERT2 mice were purchased from the Jackson Laboratory or Japan SLC, Hamamatsu. Enteroid culture. Crypt isolation and enteroid culture were performed as previously described (7). Crypts were isolated from mouse ilea by incubation for 30 minutes at 4°C in PBS containing 2 mM EDTA. A total of 50 crypts were mixed with 10 μl Matrigel Growth Factor Reduced (Corning) and plated in 96-well plates. After the Matrigel polymerized, culture medium (Advanced DMEM/F12 supplemented with 100 U/ml penicillin, 100 μg/ml streptomycin, 10 mM HEPES, 2 mM Glutamax, 1× N2 supplement, 1× B27 supplement [all from Thermo Fisher Scientific], 1 mM N-acetylcysteine [Sigma-Aldrich], 50 ng/ml mouse EGF [PeproTech], 100 ng/ml mouse Noggin [PeproTech], and 1 μg/ml human R-spondin 1 [R&D Systems]) was added. Culture media were replaced every 4 days. For passage, enteroids were removed from Matrigel and mechanically dissociated into single-crypt domains, and then transferred to fresh Matrigel. Passage was performed every 1–2 weeks, with a 1:5 split ratio. Every experiment was started on day4 after enteroid passage. For T cell coculture experiments, CD4+ and CD8+ T cells were isolated with CD4 and CD8a MicroBeads (Miltenyi Biotec) from C57BL/6 mouse splenocytes. T cells or splenocytes were cocultured at a ratio of 50,000 cells per 40–60 enteroids, which were embedded in Matrigel. T cells were activated by addition of Dynabeads Mouse T-Activator CD3/CD28 (Thermo Fisher Scientific) to cultures. For experiments evaluating the effects of cytokines on enteroids, rmIL-2, rmIL-6, rmIL-17A, rmIFN-γ, rmTNF-α were added to culture wells (BioLegend). In some experiments, enteroids were cultured in the presence of ruxolitinib (SelleckChem). To evaluate disruption of enteroid integrity, an enteroid damage scoring system was established as follows: normal condition, 1; partial disruption or loss of crypt domains, 2; enteroid dissociation >50%, 3; and complete enteroid dissociation, 4. Cytokine ELISA assay. Conditioned media were collected from enteroid cultures and stored at −20°C. Cytokine ELISA assays were performed using mouse IL-2, IL-6, IL-17A, IFN-γ, and TNF-α ELISA MAX Deluxe (BioLegend) and performed according to the manufacturer’s protocol. qRT-PCR. Total RNA was extracted using TRIzol Reagent (Thermo Fisher Scientific). cDNA was synthesized using a PrimeScript RT Reagent kit with gDNA Eraser (TaKaRa Bio). Quantitative RT-PCR was performed using a LightCycler 480 Instrument II (Roche) with LightCycler 480 SYBR Green I Master (Roche) and gene-specific primers (Supplemental Table 1). The relative amount of each mRNA was calculated by the cycling threshold (Ct) method as 2–ΔΔCt normalized to Gapdh of control samples at the same time point. Live imaging. For phase contrast microscopy, enteroids were cultured as described above. Images were captured using an Eclipse TE2000-U microscope (Nikon), SPOT RT-KE Camera, and SPOT 5.1 Advanced software (Diagnostic Instruments). For confocal time-lapse analysis, enteroids were exposed to 2 ng/ml IFN-γ with CellEvent caspase-3/7 Green Detection Reagent (Thermo Fisher Scientific) for 18 hours. Live imaging was acquired by confocal microscopy (A1, Nikon) at 37°C with 5% CO2. A Z-stack was acquired every 10 minutes for 10–16 hours. Reconstruction of images was done using NIS-Element C version 4.40 software. Histological and immunofluorescence analysis. For pathological analysis, samples of the ileum were fixed in 4% paraformaldehyde, embedded in paraffin, and examined by H&E staining and a spectrum of immunofluorescence reactions. The primary antibodies were chicken anti-GFP (1:500, ab13970, Abcam), rabbit anti-Olfm4 (1:200, D6Y5A, Cell Signaling Technology), rabbit anti–Ki-67 mAb (1:400, D3B5, Cell Signaling Technology), and rat anti-Crp1 mAb (1 μg/ml, clone 77-R63) generated following immunization of rats with synthetic mouse cryptdin-1 (32). The secondary antibodies were Alexa Fluor 488–conjugated anti-chicken IgG (A-11039), Alexa Flour 488–conjugated anti-rabbit IgG (A-11034), and Alexa Fluor 594–conjugated anti-rat IgG (A-11007) purchased from Life Technologies. Immunohistochemistry Application Solutions Kit (Rabbit) (Cell Signaling Technology) was used for IHC staining. DNA was stained by DAPI (Molecular Probes). Pictures from tissue sections were taken at room temperature using a digital camera (DS-Ri2, Nikon) mounted on a microscope (Eclipse TE2000 or A1, Nikon) and NIS-Element Br version 4.40 software. All crypts present within 50 μm of the muscularis externa were counted per ileum circumference section after staining for cryptdin-1, GFP, and Olfm4 of Lgr5-EGFP-ires-creERT2 ileum. Drug administration. Mice were injected i.p. with 50 μg mouse IFN-γ (GenScript) dissolved in 1.5 ml saline or vehicle daily in 3 equal doses every 8-hour interval for 3 days. Ruxolitinib (LC Laboratories) was dissolved in ethanol and mixed with PBS with 0.1% Tween-20. Mice received 30 mg/kg ruxolitinib p.o. in 200 μl vehicle by oral gavage 3 times per day for 3 days. The control group received vehicle alone. Irradiation and BMT. The mice were given sublethal TBI in a single 5-Gy dose using an X-RAD 320ix instrument (Precision X-Ray) 24 hours after the first administration of IFN-γ or vehicle. Then, mice were injected i.v. with 1 × 107 syngeneic bone marrow cells to rescue from bone marrow death. Mice were maintained under specific pathogen–free conditions and received normal chow and filtered water. Survival, body weight, and severity of clinical manifestations were monitored daily until 28 days after TBI. Clinical severity scores were assessed by the sum of changes in 5 clinical parameters: weight loss, posture, activity, fur texture, and skin integrity (maximum index, 10) as previously described (9). Small intestinal crypt cell preparation and flow cytometry. For crypt isolation, the villi of Lgr5-EGFP-ires-CreERT2 mouse small intestine were scraped off using a scalpel blade, and remaining tissues were washed with cold PBS. After incubation with 30 mM EDTA in HBSS for 10 minutes at room temperature, the tissue fragments were shaken vigorously in fresh HBSS to exfoliate crypts. The dissociated crypts were further digested with shaking at 180 rpm in HBSS supplemented with 300 U/ml collagenase (Sigma-Aldrich), 10 μM Y-27632 (Sigma-Aldrich), and 1 mM N-acetylcysteine for 5 minutes at 37°C on a horizontal shaker (TAITEC). Crypt cells were then briefly treated with 50 μg/ml DNase I (Roche), filtered with a 40-μm cell strainer (Corning), and washed with DMEM/F12 supplemented with 10 μM Y27632 and 1 mM N-acetyl-l-cysteine. 5 × 106 crypt cells were incubated with primary antibodies: Brilliant Violet 421–conjugated rat anti-mouse CD24 mAb (2.5 μg/ml, M1/69, BioLegend) and biotinylated hamster anti–mouse CD119 (Ifngr1) mAb (5 μg/ml, 2E2, BD Biosciences); or stained with matched isotype control IgG: Brilliant Violet 421–conjugated rat IgG Ctrl antibody (2.5 μg/ml, RTK4530, BioLegend) and hamster IgG monoclonal isotype control (5 μg/ml, 299Arm, Abcam) biotinylated with Biotin Labeling kit-NH2 (Dojindo) for 10 minutes at room temperature. After washing with sorting buffer (2% FBS in PBS), crypt cells were incubated with biotinylated goat anti-hamster IgG Ab (5 μg/ml, Poly4055, BioLegend) for 10 minutes at room temperature, washed with sorting buffer, and subsequently incubated with APC Streptavidin (5 μg/ml, BioLegend) for 10 minutes at 4°C. Cells were washed with sorting buffer, filtered with a 35-μm cell strainer (Corning), and subjected to Paneth cell and Lgr5+ ISC subpopulation analysis using a JSAN cell sorter (Bay Bioscience) and FlowJo software version 10.4.2 (TreeStar Inc.). The sorted Paneth cell subpopulation was incubated with 10 μM Zinpyr-1 (Santa Cruz Biotechnology Inc.) for 10 minutes at 37°C to stain secretory granules and identified as Paneth cells using a confocal microscope (A1, Nikon). Statistics. Groups were compared using 1-way ANOVA with Dunnett’s multiple comparisons test, 1-way ANOVA with Tukey’s multiple comparisons test, or 2-tailed unpaired t test, as indicated in the figure legends. All tests were performed with GraphPad Prism version 7 software. Statistical significance for comparisons was assigned at *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Study approval. All animal experiments were performed with approval of the Institutional Animal Care and Use Committee of University of Southern California and under the auspices of the Institutional Animal Care and Research Advisory Committee of Hokkaido University. Author contributions YE and AJO developed the conceptual framework of the study; YE designed and performed experiments and analyzed data; YE and AJO wrote the manuscript; YY, KN, RS, and ST conducted experiments; KN, TA, DH, and TT supervised experiments. MES analyzed data and edited the manuscript. Supplemental material Acknowledgments This study was supported by NIH grants R21AI105057 (AJO) and R01AI22931 (MES); a fellowship (2013-2014) from the Uehara Memorial Foundation, Tokyo, Japan (YE); Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science 26462831 (KN) and 17H04206 (TT); the Ministry of Education, Culture, Sports, Science, and Technology of Japan (TA); and the Center of Innovation Program from the Japan Science and Technology Agency (KN). This work was also supported in part by USC Norris Cancer Center Support Grant P30CA014089 from the National Cancer Institute. Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. Reference information: JCI Insight. 2018;3(18):e121886. https://doi.org/10.1172/jci.insight.121886. References Clevers HC, Bevins CL. Paneth cells: maestros of the small intestinal crypts. Annu Rev Physiol. 2013;75:289–311. 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Research ArticleImmunologyInfectious disease Free access | 10.1172/JCI121486 TNF overproduction impairs epithelial staphylococcal response in hyper IgE syndrome Ian A. Myles,1 Erik D. Anderson,1 Noah J. Earland,1 Kol A. Zarember,2 Inka Sastalla,1 Kelli W. Williams,1 Portia Gough,1 Ian N. Moore,3 Sundar Ganesan,4 Cedar J. Fowler,1 Arian Laurence,5 Mary Garofalo,2 Douglas B. Kuhns,6 Mark D. Kieh,1 Arhum Saleem,1 Pamela A. Welch,1 Dirk A. Darnell,1 John I. Gallin,2 Alexandra F. Freeman,1 Steven M. Holland,1 and Sandip K. Datta1 First published July 23, 2018 - More info Abstract Autosomal dominant hyper IgE syndrome (AD-HIES), or Job’s syndrome, is a primary immune deficiency caused by dominant-negative mutations in STAT3. Recurrent Staphylococcus aureus skin abscesses are a defining feature of this syndrome. A widely held hypothesis that defects in peripheral Th17 differentiation confer this susceptibility has never been directly evaluated. To assess the cutaneous immune response in AD-HIES, we induced suction blisters in healthy volunteers (HVs) and patients with AD-HIES and then challenged the wound with lethally irradiated bacteria. We show that cutaneous production of IL-17A and IL-17F was normal in patients with AD-HIES. Overproduction of TNF-α differentiated the responses in AD-HIES from HVs. This was associated with reduced IL-10 family signaling in blister-infiltrating cells and defective epithelial cell function. Mouse models of AD-HIES recapitulated these aberrant epithelial responses to S. aureus and involved defective epithelial-to-mesenchymal transition (EMT) rather than a failure of bacterial killing. Defective responses in mouse models of AD-HIES and primary keratinocyte cultures from patients with AD-HIES could be reversed by TNF-α blockade and by drugs with reported modulatory effects on EMT. Our results identify these as potential therapeutic approaches in patients with AD-HIES suffering S. aureus infections. Graphical Abstract Introduction Autosomal dominant hyper IgE syndrome (AD-HIES), also known as Job’s syndrome, is a primary immune deficiency caused by dominant-negative loss-of-function mutations in the STAT3 gene. Recurrent Staphylococcus aureus skin abscesses (1), reminiscent of the boils that smote the biblical figure Job, are a defining feature of this syndrome. Additional features include elevated serum IgE, atopic dermatitis, recurrent pulmonary infections, bone fragility, and vascular abnormalities, all of which may be related to impaired wound healing and tissue remodeling (1–4). When a defect in the peripheral blood CD4+ T cell production of IL- 17 was discovered in patients with AD-HIES (5), it was proposed that the patients’ increased S. aureus susceptibility might be due to reduced IL-17 production. However, the hypothesis of IL-17–mediated S. aureus defects in patients with AD-HIES has never been directly evaluated. To assess the cutaneous immune response in AD-HIES, we induced suction blisters in healthy volunteers (HVs) and patients with AD-HIES, removed the epidermal layer, and challenged the wound with lethally irradiated bacteria (6). Here, we show that cutaneous production of IL-17A, IL-17F, and most antimicrobial peptides was normal in patients with AD-HIES, suggesting an alternative mechanism of aberrant S. aureus responses. We show that overproduction of TNF-α differentiated the responses of patients with AD-HIES from those of HVs and was associated with epithelial dysfunction, as indicated by markers of epithelial-to-mesenchymal transition (EMT). These results are consistent with prior studies demonstrating intact TLR signaling and an overproduction of TNF-α after TLR stimulation in AD-HIES (7–9). Defective responses in mouse models of AD-HIES and primary keratinocyte (KC) and fibroblast (FB) cultures from patients with AD-HIES could be reversed by TNF-α blockade or by EMT modulators. Our results identify TNF-α blockade and/or EMT modulation as potential therapeutic approaches in patients with AD-HIES suffering S. aureus infections. Results An aberrant responses to S. aureus is associated with TNF-α overproduction in skin blister challenge models. Despite having colonization rates similar to those in patients with atopic dermatitis, patients with AD-HIES had significantly greater rates of S. aureus skin abscesses (94% versus 10%) and S. aureus pneumonia (42% versus 0%; Supplemental Table 1). These data confirm reports of profound S. aureus susceptibility in AD-HIES that differentiates it from atopic dermatitis. To begin to assess this susceptibility, we used a suction blister model that exposes wounded skin to either autologous serum (10) or lethally irradiated bacteria in saline diluent (6). Compared with HVs, patients with AD-HIES did not display any significant deficit of IL-17A in the initially accumulated (“neat”) blister fluid (Supplemental Figure 1A; supplemental material available online with this article; https://doi.org/10.1172/JCI121486DS1) or after exposure to 70% autologous serum (Supplemental Figure 1B). Likewise, patients with AD-HIES displayed no significant defect in the accumulation of IL-17A or IL-17F after exposure to saline (Figure 1A and Supplemental Table 2) or irradiated methicillin-resistant S. aureus (MRSA) (strain USA300 LAC) (Figure 1B and Supplemental Table 2). We performed intracellular staining on the infiltrating blister cells but were unable to identify the cellular source of IL-17. This may be indicative of technical limitations due to the predominance of neutrophils and low CD3+ T cell numbers in the blister fluid (Supplemental Figure 1, C and D), but may also suggest a cellular source in the underlying dermis. Figure 1 Human STAT3 dysfunction is associated with overproduction of TNF-α. (A–D) Twelve HVs and eight patients with AD-HIES underwent blister induction and challenge of the wounded area with lethally irradiated bacteria or diluent control. IL-17A, IL-17F (A and B), TNF-α (C), and IL-10 (D) concentrations in blister fluid after 20 hours of incubation with saline (A, C, and D) or irradiated MRSA (B–D). (E–G) Live blister-infiltrating neutrophils (1 × 105) from the blister well challenged with irradiated MRSA as in B–D (E) or peripheral neutrophils (F) were harvested from 4 HVs and 4 patients with AD-HIES. The cells were then incubated ex vivo for 48 hours with irradiated S. aureus (MOI of 10) and IL-10, IL-20, or diluent. (G) Approximately 1 × 106 primary KCs from 3 HVs or 3 with AD-HIES patients were incubated for 24 hours with irritated MRSA as in E and F. Shown is the supernatant TNF-α concentration from independent cell lines, which are indicated by individual dots. Data represent a combination of experiments involving individual patients (A–F) or are representative of 3 independent experiments (G) and are displayed as the mean ± SD. *P < 0.05, **P < 0.01, and ***P < 0.001, by ANOVA with Bonferroni’s correction versus HVs across 14 tested cytokines (A–D; see also Supplemental Figure 1 and Methods). Blister accumulation of other cytokines tested in response to autologous serum (Supplemental Figure 1, E and F), saline (Supplemental Figure 1G), or irradiated MRSA (Supplemental Figure 1H) did not differ between HVs and patients with AD-HIES. However, consistent with reports involving peripheral blood (11), patients had increased blister TNF-α concentrations in response to MRSA (Figure 1C). We observed similar but nonsignificant trends in the neat fluid and blister fluid responses to autologous serum (Supplemental Figure 1I). Prior reports involving DCs suggested that STAT3 mutations may lead to overproduction of TNF-α as a result of the STAT3 dependence of inhibitory IL-10 signaling (12, 13). We found that IL-10 accumulation in the blister fluid was equivalent between HVs and patients with AD-HIES (Figure 1D). IL-10 and IL-20, a related STAT3-dependent epithelial cytokine (14), inhibited TNF-α production in blister-infiltrating neutrophils from HVs, but not in those from patients with AD-HIES (Figure 1E). We found that IL-10 inhibited TNF-α production in both HV and AD-HIES peripheral blood neutrophils (Figure 1F), suggesting differences in responsiveness resulting from activation and/or diapedesis. Peripheral neutrophils did not respond to IL-20 (Figure 1F), consistent with their reported lack of IL-20 receptor expression (15). Primary KCs from patients with AD-HIES stimulated with irradiated S. aureus produced more TNF-α than did KCs from HVs, but IL-10– and IL-20–mediated inhibition was preserved (Figure 1G). Taken together, these results suggest that the TNF-α overproduction associated with AD-HIES may be driven by direct KC overproduction as well as failed inhibitory IL-10/IL-20 signaling in infiltrating cells. Mouse models of AD-HIES display aberrant responses to S. aureus. We next aimed to model the aberrant responses seen in patients with AD-HIES using mutStat3 mice, which contain a transgenic insertion of 2 copies of dominant-negative Stat3 to mimic the genotype of patients with AD-HIES (16). Consistent with the clinical presentation of AD-HIES, mutStat3 mice had larger lesion sizes than did WT littermate mice (Figure 2A). They also had an increased abundance of TNF-α transcripts in S. aureus–infected skin (Figure 2B), similar to our human blister data. MutStat3 mice had a lower abundance of IL-17A transcripts (Figure 2B); however, bacterial numbers did not differ from those in WT mice in the skin or kidneys (a prominent site of dissemination; ref. 17 and Figure 2, C and D), suggesting that there was no dramatic defect in bactericidal mechanisms. Figure 2 MutStat3 mice have a defect in their cutaneous response to S. aureus. (A) Littermate WT mice or mice with a transgenic insertion of mutated Stat3 (mutStat3) were infected with 107 CFU MRSA by s.c. injection, and the lesion area was measured daily. (B) Transcript levels from homogenized skin harvested on day 5 or 6 in mutStat3 mice relative to WT (set to 1, dotted line), normalized to GAPDH, are shown for IL-1β, IL-17A, and βD4. (C) A 3-mm biopsy was taken from infected skin, and (D) the kidneys were collected on day 5 or 6 and homogenized and plated after serial dilutions to enumerate the CFU burden. (E and F) Transcript values, as in C, were normalized to GAPDH and are relative to WT. Data shown are a combination of 3 or more independent experiments and displayed as the mean ± SD. n = 4–7 mice per group, per experiment. *P < 0.05 and ***P < 0.001, by ANOVA with Bonferroni’s correction. We speculated that known defects in wound healing and tissue remodeling in AD-HIES (1–4), rather than direct bactericidal defects, may contribute to the aberrant responses to S. aureus. EMT is an essential process in wound healing that is influenced by multiple interlinked signaling pathways, including STAT3, Wnt/β-catenin, and TNF-α (18–21). In line with the hypothesis of an EMT defect in AD-HIES, S. aureus–infected mutStat3 mice had reduced transcript levels of Wnt5a (Figure 2E), which has been reported to inhibit TNF-α production from human retinal pigment epithelial cells (22). Furthermore, mutStat3 mice had reduced transcript levels of other EMT markers, including vimentin, an intermediate filament enhanced by STAT3 activation (ref. 23 and Figure 2F). Bone marrow transplantation failed to rescue lesion size defects in mutStat3 mice (Supplemental Figure 2), further suggesting potential epithelium-mediated pathology. Reduced EMT activation in AD-HIES is consistent with the clinical practice of inhibiting STAT3 as a therapeutic means of inhibiting EMT in the treatment of cancer (21). However, TNF-α has been described as an inducer of EMT (24), and thus evidence of reduced EMT activation in the presence of elevated TNF-α is an unexpected finding. This paradoxical result may reflect hormetic behaviors of high-dose TNF-α (25), or signaling defects specific to STAT3 mutation that lead to defective EMT (18, 19). AD-HIES is associated with defects in cell cultures of tissue remodeling. While bone marrow transplantation failed to rescue the anti–S. aureus response in mutStat3 mice, we found that transplantation of mutStat3 bone marrow into WT mice worsened the outcomes (Supplemental Figure 2). Additionally, clinical bone marrow transplantation has shown variable efficacy in treating the epithelial manifestations of AD-HIES (26–30). Taken together, these data suggest that hematopoietic cells are necessary but insufficient for normal tissue responses to infection. We therefore hypothesized that dysfunction in nonhematopoietic epithelial tissue may be an independent driver of pathology. To evaluate epithelial morphogenesis, we used human organotypic skin cultures formed by seeding KCs on top of FBs and allowing for self-organization into both dermal and epidermal layers (31). Compared with HV-sourced cells, organotypic cultures from AD-HIES patients failed to correctly organize into the expected epithelial layers (Figure 3A). We observed disordered organization when either KCs or FBs were sourced from patients with AD-HIES (Figure 3A). Figure 3 Skin cell cultures from patients with AD-HIES display TNF-α–sensitive defects in wound healing). (A) 3D organotypic cultures of KCs and FBs from HVs and patients with AD-HIES. (B) IF images (original magnification, ×20) for DAPI (blue) and vimentin (red) and (C) mean intensity of the IF signal of the leading edge of the scratch assay monolayer culture of dermal FBs from HVs and AD-HIES patients. (D) IF images of organotypic cultures, as in A, stained for β-catenin (red), vimentin (green), and DAPI (blue). FBs and KCs were sourced from both HVs and AD-HIES patients, as indicated. Scale bars: 40 μm. (E) Western blot of nuclear and cytoplasmic fractions from KCs obtained from HVs and AD-HIES patients (KCs were cultured with TNF-α or diluent). (F) Band intensity for β-catenin, as in E, normalized to either a histone 3 (nuclear) or β-actin (cytoplasmic) loading control. (G) Area of coverage after 18 to 22 hours of incubation in a scratch assay for KCs (see Supplemental Video 1) and FBs (see Supplemental Video 2). Data are representative of 3 or more independent experiments and displayed as the mean ± SD. n = 3 cell lines per group, indicated by individual dots. Each experiment used at least 2 different cell lines assayed in duplicate. *P < 0.05, **P < 0.01, and ****P < 0.0001, by ANOVA with Bonferroni’s correction, compared with diluent treatment (F), or as indicated. Dil., diluent. To further characterize this disordered epithelial organization, we assessed markers of EMT in the organotypic cultures. In accordance with our mouse data (Figure 2F), vimentin signal was reduced in AD-HIES FBs, TNF-α–treated HV FBs (Figure 3, B and C), and in the basal layer of AD-HIES KCs in the organotypic cultures (Figure 3D). A shift from cytoplasmic to nuclear localization of β-catenin is another marker of EMT (20). Consistent with reduced EMT activity, AD-HIES–sourced KCs showed reduced nuclear β-catenin signal (Figure 3, E and F). Similarly, AD-HIES FBs had reduced expression of the β-catenin complex N-cadherin (Supplemental Figure 3, A and B). In a scratch assay (32) model of dynamic wound healing, we further found disorganized and deficient cell healing and migration in AD-HIES–sourced KCs (Supplemental Video 1 and Figure 3G), AD-HIES–sourced FBs (Supplemental Video 2 and Figure 3G), and TNF-α–treated HV FBs (Supplemental Video 3 and Supplemental Figure 3C) Blockade of TNF-α rescues aberrant anti–S. aureus responses in mutStat3 mice. Preclinical evaluation of TNF-α blockade reversed pathological responses to cutaneous S. aureus infection in mutStat3 mice as measured by lesion size (Figure 4, A and B); histologic evidence of epidermal inflammation (Figure 4C); the expression of β-catenin and vimentin in the dermis (Figure 4D and Supplemental Figure 3D); and transcript abundance of IFN-γ and IL-17A (Supplemental Figure 3E). Beneficial effects were also found in a S. aureus pneumonia model, in which TNF-α blockade rescued mutStat3 lung pathology, characterized by multifocal and coalescing regions of intense lymphohistiocytic and eosinophilic perivascular-to-interstitial inflammation (Figure 4E) that was associated with reduced vimentin signal in the infected tissue (Figure 4F). Similar treatment effects were seen with clofazimine or rosiglitazone (Supplemental Figure 4 and Supplemental Videos 1 and 2), two unrelated drugs with reported off-target effects on EMT (33) that may provide alternative therapeutic strategies that avoid the potential increased risk of mycobacterial infection associated with anti–TNF-α therapy (34). Figure 4 TNF-α blockade rescues aberrant anti–S. aureusresponses in mutStat3 mice. (A–D) Littermate WT and mutStat3 mice were treated with daily i.p. injections of anti–TNF-α or isotype control for 4 days prior to s.c. infection with 106 CFU MRSA (n = 3–5 mice per group). The mean resultant lesion area over time (A), as well as day-5 images of skin lesion (B), H&E histology (original magnification, ×20) (C), and IF staining (original magnification, ×10) (D) from the median mouse in each group. (E and F) WT and mutStat3 mice were treated with anti–TNF-α as above before nasal inoculation with 108 CFU MRSA. H&E histological images from day 7 (original magnification, ×40) (E) and IF images (original magnification, ×20) (F) of lung. Data are representative of 3 or more independent experiments and displayed as the mean ± SD. *P < 0.05 and **P < 0.01, by ANOVA with Bonferroni’s correction versus WT diluent– or isotype-treated control. Discussion Our results suggest that overexpression of TNF-α and disordered EMT induction may contribute to aberrant S. aureus responses in AD-HIES. These findings do not exclude the possibility of a contribution of IL-17 defects to S. aureus susceptibility. The preserved cutaneous IL-17 production seen in patients with AD-HIES should be interpreted cautiously, since we evaluated production up to 20 hours after challenge, potentially before adaptive T cell cytokine deficiencies may be detectable. The decreased IL-17 we observed in mutStat3 mice 5–6 days after infection may reflect this kinetic issue or may indicate that cutaneous IL-17 production is γδT cell predominant in mice versus αβT cell predominant in humans (35). Our findings distinguish patients with AD-HIES from those with isolated IL-17 receptor defects or gain-of-function STAT1 mutations, in whom defective IL-17 signaling has not been associated with TNF-α overproduction and confers infectious susceptibilities more predominated by Candida albicans than S. aureus (36, 37). Furthermore, elevated TNF-α in the context of hypomorphic STAT3 contrasts AD-HIES with psoriasis, in which elevated cutaneous levels of TNF-α (38) are associated with hyperactivity of STAT3 (39, 40). Failed signaling of IL-10 family cytokines in responding leukocytes appears to contribute to the observed TNF-α overproduction, as may other signaling defects associated with STAT3 mutations (41). Our data suggest that the defects associated with EMT pathways in dermal FBs from AD-HIES patients may be partially mediated by Wnt signaling abnormalities and potentially exacerbated by excess TNF-α exposure. Similarly, AD-HIES KCs show defects in cell migration and reduced acquisition of EMT markers associated with abnormal β-catenin localization. Reduced EMT activation in AD-HIES is consistent with the known anti-EMT effects of STAT3 inhibition (21) and the reported STAT3 dependence of select EMT pathways (42, 43). However, additional inquiry will be required to identify how AD-HIES mutations in STAT3 alter EMT activation. The observed defects in EMT and β-catenin localization could conceivably affect the function of a wide variety of tissues (44), thereby contributing to the multisystem clinical spectrum seen in AD-HIES. However, tissue-specific differences in EMT pathways also indicate that extrapolation of our findings to other infection models or other diseases should be done cautiously, especially given that subtle differences in EMT markers and TNF-α sensitivity could be seen between FBs and KCs in our experiments. Overall, our findings suggest that both overproduction of and paradoxical responses to TNF-α exposure contribute to epithelial dysfunction in patients with AD-HIES. Further mechanistic insight is needed to fully elucidate the role of STAT3 in EMT and epithelial function, but the reversal of pathology with TNF-α blockade and drugs with reported modulatory effects on EMT in mutStat3 mice and AD-HIES cell culture systems represent promising preclinical findings. Additional studies will be required to assess whether these treatments can provide equivalent benefit when initiated after the onset of inflammatory pathology. Ultimately, our results suggest that abnormalities in epithelial responses, including EMT and associated TNF-α overproduction, may underlie the aberrant responses to S. aureus in patients with AD-HIES and that pharmaceutical intervention targeting these pathways may benefit this unique patient population. Methods Human subjects. Patients with AD-HIES and HVs were recruited to participate in this study at the NIAID under IRB-approved protocols (NCT02262819 and NCT00001257). A total of 36 patients with AD-HIES were enrolled in the studies. Under protocol NCT00001257, five AD-HIES patients and twenty-one HVs underwent suction blister induction, and, after collection of the initially accumulated (neat) blister luminal fluid and removal of the epidermis, the wounds were challenged with 70% autologous serum (t0), and the subsequently accumulated fluid was collected sixteen hours later (t16). Under NCT02262819, eight patients underwent blister induction, and the blister wounds were challenged with lethally irradiated bacteria for twenty hours prior to collection of the accumulated blister fluid; these patients also had their skin swabbed to assess S. aureus colonization. CFU equivalents (2 × 107) of lethally irradiated S. aureus (strain USA300 LAC) were used for the bacterial challenge. The remaining 18 patients only had their skin swabbed to assess S. aureus colonization. A total of 47 HVs enrolled in the studies, 21 of whom underwent blister induction and challenge with 70% autologous serum (NCT00001257). An additional 12 HVs underwent blister induction, challenge with lethally irradiated bacteria, and assessment for S. aureus colonization (NCT02262819). The remaining 14 HVs only had their skin swabbed to assess S. aureus colonization. Skin bacteria isolation and culture were performed as previously described (45). Blisters were induced, and the subsequent cell infiltrate and cytokine concentrations in the blister fluid were determined as previously described (6, 46). Cell viability was approximately 50% in both groups as determined by LIVE/DEAD staining (BD Biosciences). The rates of infections of S. aureus skin abscess and pneumonia were determined by chart review. Twenty patients with non–AD-HIES atopic dermatitis were recruited under the IRB-approved protocol NCT01164241. Mice. Experiments were performed in both male and female mice but were age and se matched within each experiment. WT C57BL/6 mice were purchased from The Jackson Laboratory. MutStat3 mice (C57BL/6-Tg(Stat3*)9199Alau/J) were a gift from Liana Falcone (NIAID, NIH) and Josh Milner (NIAID, NIH) or were purchased from The Jackson Laboratory. Littermate control mice were used as indicated in the text. Skin infections, CFU assessment, and PCR on skin were all performed as previously described (14). Bone marrow transplantation was performed as previously described (16). For anti–TNF-α treatment, mice were injected i.p. with 4 mg/kg anti–TNF-α (R&D Systems; catalog AB-410-NA) or goat IgG isotype (R&D Systems) daily for 4 days. The following day, mice were challenged with S. aureus. Skin CFU assessment and mRNA transcript evaluations were performed as previously described (14). Mice treated with clofazimine (Sigma-Aldrich) and rosiglitazone (Cayman Chemical) received daily gavage beginning 3 days before and up through the day of the infection (days –3 to 0). Clofazimine was suspended in 1:1 DMSO and 100% ethanol to 150 mg/ml, and this stock was diluted to 7.5 mg/ml in 5% w/v agarose in sterile water. Rosiglitazone was suspended in 1:1 DMSO and 100% ethanol to 50 mg/ml, and this stock was diluted to 2.5 mg/ml in sterile water. A dose of 100 μl each of clofazamine and rosiglitazone was administered. KC culture. KCs were cultured with irradiated 3T3-J2 FBs in feeder medium containing 3:1 (v/v) Ham’s F-12 Nutrient Mix (Invitrogen, Thermo Fisher Scientific) containing DMEM high glucose no glutamine (Invitrogen, Thermo Fisher Scientific), 5% newborn calf serum (Thermo Fisher Scientific), 0.4 μg/ml hydrocortisone (Sigma-Aldrich), 5 μg/ml insulin, 8.4 ng/ml cholera toxin, 10 ng/ml EGF (Invitrogen, Thermo Fisher Scientific), 24 μg/ml adenine, 10 U/ml penicillin and 10 μg/ml streptomycin, 2 mM L-glutamine (Gibco), 100 μg/ml Primocin (Invitrogen), and 10 μM Y-27632 (Tocris). Y-27632 is a Rho kinase inhibitor, and its use in KC culture has been described previously (47, 48). 3T3-J2 feeder FBs were subcultured in DMEM (1×) with GlutaMAX (Invitrogen, Thermo Fisher Scientific), 10% FBS (Hyclone), 25 mM HEPES, and 50 μg/ml gentamicin. FBs were cultured in 175-cm2 flasks at an initial density of 2 × 106 cells and passed every 3 days using 0.25% trypsin-EDTA to detach cells. Prior to coculture with the KCs, 3T3-J2 cells were γ-irradiated with a dose of 60 Gy. Cocultured cells were passed using versene to detach the FB feeder cells, followed by 0.25% trypsin-EDTA to detach the KCs. After detachment, the KCs were passed through a 70-μm nylon filter to break up cell aggregates and then seeded in a 10-cm dish at a density of 4 × 105 KCs/1 × 106 3T3-J2 FBs. Primary FB culture. Primary dermal FBs were cultured in Corning 162-cm2 flasks in culture medium consisting of high glucose DMEM with GlutaMAX supplement, penicillin, streptomycin, and 10% FBS (FB DMEM complete). Once cells reached 70%–90% confluency, they were washed with PBS and harvested using 7 ml of a 0.25%Trypsin/EDTA solution, before being reneutralized with 8 ml FB DMEM complete and pelleted via centrifugation at 1,200 g. The neutralization media were discarded before the cells were resuspended in FB DMEM complete, counted with trypan blue exclusion on a hemocytometer, and either split between flasks at a concentration of 5 × 105 cells/ml or plated for experimental use. Cells were split and passaged every 3 to 4 days. Organotypic raft cultures. Organotypic raft culturing was performed as previously described, with modifications (49). Primary FBs (2 × 105) from either HVs or patients with AD-HIES were seeded in 100% type 1A rat-tail collagen (Corning) with 2 × 105 primary KCs from either HVs or patients with AD-HIES and seeded in a 24-well cell culture plate with 1 ml raft medium (3:1 Ham’s F12 Nutrient Mix, Invitrogen, Thermo Fisher Scientific) containing DMEM High Glucose No Glutamine (Invitrogen, Thermo Fisher Scientific), 5% newborn calf serum (Thermo Fisher Scientific), 0.4 μg/ml hydrocortisone (Sigma-Aldrich), 10 ng/ml human EGF (Invitrogen, Thermo Fisher Scientific), 0.1 nM cholera toxin, 5 μg/ml insulin, 2 mM glutamine (Gibco, Thermo Fisher Scientific), and 100 μg/ml Primocin (Invitrogen, Thermo Fisher Scientific) and incubated overnight at 37°C and 5% CO2. The next day, the rafts were lifted onto a stainless-steel metal mesh and incubated in 6-well cell plates at the liquid-air interface for 13 days. Approximately 3 ml raft medium was used for each raft and changed every 2 days. After 13 days, the rafts were washed with PBS , fixed in formalin, and processed as described in the Immunofluorescence microscopy section of Methods. KC and FB cytokine induction assays. Primary KCs were seeded in 2 types of media for these assays: SFM(+) containing Serum-Free Medium (SFM) (Gibco, Thermo Fisher Scientific) supplemented with 10 ng/ml EGF, 50 μg/ml Bovine Pituitary Extract (BPE), 100 μg/ml Primocin, and 10 μM Y-27636; or SFM(–), containing SFM with 50 μg/ml BPE and 100 μg/ml Primocin. On day 0, cells were seeded in 1 ml SFM(+) at a density of 2 × 105 cells/well in a 24-well cell culture plate and incubated at 37°C with 5% CO2 for 24 hours. On day 1, cells were washed 3 times with PBS, incubated briefly, agitated with 0.5 ml versene, and washed again 3 times with PBS followed by addition of 1 ml SFM(–). Cells were then incubated again at 37°C and 5% CO2 for 24 hours. On day 2, cells were first washed with PBS 3 times, and then 400 μl SFM(–) containing the treatment was added. For FBs, on day 0, cells were seeded in 1 ml FB DMEM complete at a density of 2 × 105 cells/well in a 24-well cell culture plate and incubated at 37°C with 5% CO2 for 24 hours. On day 1, the FBs were washed with PBS and incubated in DMEM with GlutaMAX supplement, penicillin, and streptomycin only (FB SFM) for another 24 hours at 37°C and 5% CO2 for 24 hours. On day 2, cells were washed again with PBS and then received 400 μl FB SFM–containing treatments. For the human β-defensin induction assay, the treatments were a combination of 10 ng/ml IL-17A (R&D Systems) and IFN-γ (R&D Systems) or 0.1% BSA in PBS (no-treatment control). For the β-catenin and vimentin induction assay, the treatments were 2 ng/ml TNF-α (R&D Systems) or 0.1% BSA in PBS. Cells were incubated at 37°C and 5% CO2 for 48 hours, after which RNA, protein, or supernatant was collected. Immunoblot analysis. Protein was isolated using the NE-PER Kit (Thermo Fisher Scientific) following the manufacturer’s instructions. Protein amounts were quantified using the Pierce BCA assay (Thermo Fisher Scientific). Protein (2 μg/sample) was loaded into a 1.5-mm, 10-well NuPAGE 4%–12% Bis-Tris Gel (Thermo Fisher Scientific) and imaged using an Odyssey 3034 (LI-COR Biosciences). Integrated densitometry was calculated using ImageJ software (NIH). The following antibodies were used: β-catenin (E-5, Santa Cruz Biotechnology, catalog sc-7964; 1:50); vimentin (Life Technologies, Thermo Fisher Scientific, catalog MA5-11883; 1:50); histone H3 (D1H2, Cell Signaling Technology, catalog 44996; 1:500); β-actin (13E5, Cell Signaling Technology, catalog 4970S; 1:1,000); Rabbit IgG (H&L) Antibody DyLight 800 Conjugated (Rockland, catalog 611-145-002; 1:10,000); and Mouse IgG (H&L) Antibody DyLight 680 Conjugated (Rockland Antibodies and Assays, catalog 610-444-002). Real-time relative reverse transcription PCR. Real-time relative reverse transcription PCR (RT-PCR) was performed using the Applied Biosystems 7500 Fast Real-time PCR system as previously described (14). The TaqMan One-Step Real-Time RT-PCR Kit (Thermo Fisher Scientific) was used to detect mRNA expression of human GAPDH (Thermo Fisher Scientific, Hs02758991_g1) and hBD2 (Thermo Fisher Scientific, Hs04194486_g1). Mouse primers were also purchased from Thermo Fisher Scientific as described previously (14), with additional markers including Pparg (Mm00440940_m1); Wnt3a (Mm00437337_m1); Wnt5a (Mm00437347_m1); Wnt6 (Mm00437353_m1); Fzd1 (Mm00445405_s1); Fzd9 (Mm01206511_s1); vimentin (Mm00619195_g1); Twist1 (Mm00442036_m1); Snail1 (Mm00441533_g1); Slug (Mm00441531_m1); and Zeb1 (Mm00495564_m1). ELISA. hBD2 was quantified using the Human BD2 Standard TMB ELISA Development Kit (PeproTech) according to the manufacturer’s instructions, with minor alterations. A streptavidin concentration of 0.5 μg/ml was used, and the color was allowed to develop for 10 minutes after addition of tetramethylbenzidine (TMB). Cytokine concentrations for Supplemental Figure 1, A, B, E, and F were determined using custom plates for the indicated analytes (Meso Scale Diagnostics). Fluorescence microscopy scratch assay. Coverslips (15-mm) were placed inside each well of two 24-well plates, one designated t0 and the other t18. KCs were seeded at a density of 2 × 105 cells/well in SFM(+) at 37°C. After 24 hours, the media were replaced with SFM without EGF and Y-27632 SFM(–), and for those media that received 2 μg/ml clofazimine (Sigma-Aldrich) and 3.5 μg/ml rosiglitazone (Cayman Chemical) in advance of TNF-α (R&D Systems), the supplements were added at this point, and then both plates were incubated for another 24 hours at 37°C. The next day, the cells were washed with PBS and the media replaced with SFM(–) containing the appropriate amounts of the following: 2 μg/ml clofazimine, 3.5 μg/ml rosiglitazone, 20 ng/ml TNF-α, or 0.05% ethanol to serve as the diluent control. The cells were incubated for another 24 hours at 37°C, and the next day, the cells were washed with PBS and 0.5 ml of 10 μg/ml mitomycin C for 2 hours at 37°C. Next, the media were replaced with PBS, and using a 200-μl RAININ pipette tip, a scratch was made lengthwise down the well spanning the entire diameter. The cells were then washed 3 times with PBS, and 3.7% formaldehyde in PBS was added to the plate designated t0. SFM(–) media were added to the t18 plate and placed back into the 37°C incubator for 18 hours. Following this, the media were aspirated and replaced with 3.7% formaldehyde in PBS. For FBs, the same general procedure was followed, except the cells were seeded in FB DMEM complete media for 24 hours, which was then replaced with DMEM complete containing each treatment supplemented in the media. The immunostaining procedure began by washing the coverslips in PBS, followed by permeabilization for 5 minutes in 0.1% Triton X-100 in PBS. Cells were then blocked for 1 hour at room temperature in 3% BSA with 1% FBS and 0.1% Tween-20 in PBS, followed by incubation overnight at 4°C with a primary antibody for β-catenin (Santa Cruz Biotechnology, catalog sc-7963) or vimentin (Life Technologies, Thermo Fisher Scientific, catalog MA5-11883; 1:50). The next day, the cells were washed in 0.05% Tween-20 in PBS and then incubated for 1 hour at room temperature with the secondary antibody goat anti-mouse IgG AF594 (Thermo Fisher Scientific, catalog A-11005). The cells were then washed again in the 0.05% Tween-20/PBS mixture and then incubated with 300 nM DAPI (Thermo Fisher Scientific) for 5 minutes. The slides were mounted using Thermo PermaFluor and imaged using a Leica DMI6000 Inverted Fluorescence Microscope equipped with a Leica DFC345 Monochrome camera and using LAS X software for data collection (original magnifications of ×10 and ×63 were used). Percentage of coverage determined by fluorescence: DAPI-stained cells within an area measuring 838 × 698 μM2 in each image were counted using Imaris 9.0. The percentage of coverage was determined as follows: T18 = Average cell number from hour-18 slide scratch area (n = 5) T0 = Average cell number from hour-0 slide scratch area (n = 5) TAvg = Average cell number from hour-18 slide nonscratch area (n = 3) (Equation 1) Light microscopy scratch assay. The light microscopy scratch assay was performed similarly to the fluorescence assay, except that only single plates were used instead of duplicate plates. Before the cells are seeded, the 24-well plate was prepared by etching a line on the bottom of the plate across the width of each well (0.5 cm down from the top of the well) to provide a reference point for subsequent images. Images were taken with a Zeiss Axiovert 200 using an exposure time of 700 ms just after the scratch was made at t0, and then again after 18 hours of 37°C incubation. The original magnification used to image the cells was ×2.5. Live imaging scratch assay. The setup and treatment concentrations were the same as those described in the fluorescence microscopy scratch assay, except that only one 24-well plate was used instead of two. After the scratch was made, the cells were placed in a container on a movable stage that was kept at 37°C and 5% CO2. Two positions were programmed for each well using the LAS X program, and a ×10 image was taken every 10 minutes for 22 hours. The images were compiled into a movie using Imaris 9.0, which was also used to calculate the percentage of wound healing. The total surface area of the scratch at both the beginning and the end of the 22-hour period was measured using the “insert surface” feature. Then, the 22-hour surface area was divided by the 0-hour surface area, which gave the percentage of change in wound area. This change in wound area was subtracted from 100% to give the relative percentage of wound healing in each condition for each cell line. Immunofluorescence microscopy of paraffin-embedded tissue. Tissue sections were fixed in formalin and sent to Histoserv Inc. for processing. Sections were deparaffinized with three 3-minute washes with Xylene substitute (Thermo Fisher Scientific, catalog 9990505). Following this, tissue was washed with three separate 3-minute washes in 100% dehydrant (Thermo Fisher Scientific, catalog 22050106), and then one 3-minute wash in 95% dehydrant (Thermo Fisher Scientific, catalog 22050107). Tissue was then rinsed with tap water and submerged in deionized water briefly, heat-induced antigen retrieval was performed on the tissue using epitope retrieval solution, pH 6 (Leica, catalog RE7113-CE), and an Instant Pot pressure cooker was set on “soup” at high pressure for 40 minutes. Slides were then washed in PBS for 5 minutes, permeabilized with 0.1% Triton X-100 in PBS for 10 minutes, and blocked in 3% BSA with 1% FBS and 0.1% Tween-20 in PBS for 2 hours at room temperature. Next, the primary antibody targeting β-catenin (Santa Cruz Biotechnology, catalog sc-7963) was added at a concentration of 4 μg/ml blocking solution and incubated overnight at 4°C. Following this, the slides were washed 3 times with 0.1% Tween-20 in PBS, and the secondary antibody goat anti-mouse IgG AF594 (Thermo Fisher Scientific, catalog A-11005) was added at a concentration of 10 μg/ml in the blocking solution and incubated at room temperature for 2 hours. DAPI was added at a concentration of 300 nM for 10 minutes, and following this, the slides were washed again 3 times with.1% Tween-20 in PBS and then mounted using Lab Vision PermaFluor (Thermo Fisher Scientific). The slides were imaged as described in the Fluorescence microscopy scratch assay section of Methods. Statistics. Means were compared by unpaired, 2-tailed t test or by ANOVA for comparisons of multiple samples, using GraphPad Prism (GraphPad Software). Bonferroni’s correction for Figure 2, A–C, accounted for the 14 analytes in the multiplex assay. A P value of less than 0.05 was considered statistically significant. Study approval. Studies in humans were conducted under the registered clinical trials NCT02262819 and NCT00001257 (www.clinicaltrials.gov) after approval from the IRB of the NIAID, NIH. Patients with non–AD-HIES atopic dermatitis were recruited under the NIAID IRB–approved protocol NCT01164241. All subjects provided informed consent prior to their participation in the study. All murine experiments were performed in compliance with the guidelines of the IACUC of the NIAID, NIH. Author contributions IAM designed the studies, performed and analyzed experiments, and wrote the manuscript. EDA and NJE designed, performed, and analyzed select experiments and wrote the manuscript. KAZ designed and conducted experiments involving autologous serum wound challenge. IS designed and performed experiments related to KC cultures. KWW evaluated patients and assisted in the collection of clinical samples. PG conducted flow cytometry on blister-infiltrating cells. INM performed pathologic evaluations of all H&E-stained samples. SG assisted with immunofluorescence (IF) staining and imaging. CJF designed and performed select mouse infection experiments. AL assisted with mutStat3 mice experiments and performed bone marrow transplantations. MG performed wound challenges involving autologous serum. DBK performed cytokine analysis on samples challenged with autologous serum. MDK and AS assisted with select experiments. PAW and DAD provided administrative support for all patients and HVs enrolled in the protocol. JIG, AFF, and SMH provided clinical supervision for all patients. SKD oversaw the project and wrote the manuscript. All authors critically reviewed the manuscript. Supplemental material Acknowledgments We would like to thank the patients, their families, and the healthy participants for their assistance. We thank the NIAID veterinarians and animal care and breeder technicians, as well as U. Topolino and N. Topolino (NIAID) for their cooperation and sacrifice during the course of this project. This work was supported by the Intramural Research Program of the NIAID and the NIH. This project was also funded in part with federal funds from the National Cancer Institute (NCI), NIH (contract HHSN261200800001E). The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of commercial products imply endorsement by the US Government. Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. Reference information: J Clin Invest. https://doi.org/10.1172/JCI121486. References Farmand S, Sundin M. Hyper-IgE syndromes: recent advances in pathogenesis, diagnostics and clinical care. Curr Opin Hematol. 2015;22(1):12–22. View this article via: PubMed CrossRef Google Scholar Freeman AF, Olivier KN. Hyper-IgE syndromes and the lung. Clin Chest Med. 2016;37(3):557–567. 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Research ArticleInfectious diseaseTherapeutics Free access | 10.1172/jci.insight.97844 Enhancing IgG distribution to lung mucosal tissue improves protective effect of anti–Pseudomonas aeruginosa antibodies M. Jack Borrok,1 Antonio DiGiandomenico,2 Nurten Beyaz,1 Gabriela M. Marchetti,1,3 Arnita S. Barnes,1 Kristen J. Lekstrom,1 Sandrina S. Phipps,1 Michael P. McCarthy,2 Herren Wu,1 William F. Dall’Acqua,1 Ping Tsui,1 and Ruchi Gupta3 First published June 21, 2018 - More info Abstract IgG antibodies are abundantly present in the vasculature but to a much lesser extent in mucosal tissues. This contrasts with antibodies of the IgA and IgM isotype that are present at high concentration in mucosal secretions due to active delivery by the polymeric Ig receptor (pIgR). IgG is the preferred isotype for therapeutic mAb development due to its long serum half-life and robust Fc-mediated effector function, and it is utilized to treat a diverse array of diseases with antigen targets located in the vasculature, serosa, and mucosa. As therapeutic IgG antibodies targeting the luminal side of mucosal tissue lack an active transport delivery mechanism, we sought to generate IgG antibodies that could be transported via pIgR, similarly to dimeric IgA and pentameric IgM. We show that an anti–Pseudomonas aeruginosa IgG fused with pIgR-binding peptides gained the ability to transcytose and be secreted via pIgR. Consistent with these results, pIgR-binding IgG antibodies exhibit enhanced localization to the bronchoalveolar space when compared with the parental IgG antibody. Furthermore, pIgR-binding mAbs maintained Fc-mediated functional activity and promoted enhanced survival compared with the parental mAb in a P. aeruginosa acute pneumonia model. Our results suggest that increasing IgG accumulation at mucosal surfaces by pIgR-mediated active transport can improve the efficacy of therapeutic mAbs that act at these sites. Introduction Immunoglobulin isotype classes (IgG, IgA, IgM, IgD, and IgE) have distinct roles in humoral immunity and are distributed differently throughout the body. Of these, the IgG isotype is overwhelmingly favored for therapeutic mAbs for numerous reasons. Primarily, the neonatal Fc receptor (FcRn) confers long serum half-life, and Fcγ receptors (FcγRs) impart immune effector function to IgG antibodies exclusively. Additionally, the production, purification, and overall manufacturability properties of IgG mAbs are considered superior to other isotypes, which generally exhibit more complex oligomerization and glycosylation patterns. The clinical preference for the IgG isotype limits therapeutic antibodies to certain types of (FcγR-mediated) immune engagement and governs distribution throughout the body. IgG cannot be secreted to mucosal tissues like IgA and IgM, and it must rely on passive transport or transudation to accumulate at these sites. Many IgG antibodies approved or under clinical evaluation treat diseases affecting mucosal organs. These include antibodies targeting pulmonary diseases caused by viruses or bacteria (1–3), as well as other respiratory (4) and intestinal diseases (5). For therapeutic antibodies targeting antigens located in these tissues, the mainly vascular distribution of IgG could be unfavorable compared with IgA and IgM, which can be transported into the mucosal lumen at high levels. Indeed, systemically administered IgG levels in bronchoalveolar lavage (BAL) fluid have been reported to be approximately 1,000 times lower than levels of IgG in serum (6–8). The polymeric Ig receptor (pIgR) facilitates the conversion of dimeric IgA (dIgA) and pentameric IgM to their secreted forms (sIgA and sIgM), while transporting these molecules from the lamina propria of mucosal tissues to the lumen (9, 10). The secretory forms of IgA and IgM differ from those found in serum in that the extracellular portion of pIgR (after facilitating luminal transport) is proteolytically cleaved and remains bound to these Ig as the secretory component (11). The secretory component confers stability and protease resistance to IgA in the mucosal environment and enhances the protective ability of these molecules (12–14). In this study, we sought to determine whether the distribution and efficacy of an IgG antibody could be altered by endowing it with the ability to bind and be transported by pIgR. We chose Cam-003, a human IgG mAb that targets the polysaccharide synthesis locus (Psl) exopolysaccharide of Pseudomonas aeruginosa (P. aeruginosa) (15), as our model therapeutic antibody. P. aeruginosa is an important respiratory pathogen and a significant cause of acute pneumonia in ventilated subjects. In addition, P. aeruginosa is also a major cause of chronic lung infections in cystic fibrosis patients and leads to persistent lung function damage, ultimately causing death in this patient population. Psl is a serotype-independent exopolysaccharide produced by P. aeruginosa that mediates attachment to epithelial cells and is important in the formation and maintenance of antibiotic recalcitrant biofilms (16, 17). In addition, Psl prevents complement deposition on the bacterial surface, thus allowing P. aeruginosa to escape immune recognition by host effector cells (18, 19). Cam-003 targeting of Psl mediates potent complement-dependent opsonophagocytic killing (OPK) of P. aeruginosa by host effector cells and confers significant protective activity against diverse P. aeruginosa strains in a murine lung infection model (15). In this work, we show that Cam-003 fused to pIgR-binding peptides binds to pIgR and undergoes pIgR-mediated transcytosis. In addition, i.v. administration of the mAb in mice resulted in greater accumulation of pIgR peptide–fused antibodies in BAL fluid when compared with the parental IgG mAb. Consistent with these results, i.v. administration of pIgR peptide–fused Cam-003 to mice 24 hours before infection resulted in enhance survival against lethal P. aeruginosa lung infection compared with animals receiving the parental Cam-003 mAb. Our results demonstrate that conferring therapeutic IgG antibodies with pIgR binding capabilities could enhance the accumulation of therapeutic IgG antibodies targeting bacteria to the lung lumen. Results Generation and characterization of pIgR-binding peptide antibody fusions. Peptides have previously been identified that bind to pIgR and promote transcytosis of phage particles or other cargo (20, 21). To assess whether addition of these peptides to IgGs can alter antibody biodistribution, several of these peptides were generated as C-terminal fusions to the heavy chain of Cam-003 (a human IgG1 antibody that binds to the Psl exopolysaccharide of P. aeruginosa) (15). A GGGGS linker was employed to link the C-terminus of the antibody with the peptides tested. Several peptides known to bind pIgR (20, 21), as well as full-length human and mouse J-chains (known to facilitate pIgR binding in IgA and IgM), were constructed. Many of the antibody-peptide fusions (including the J-chain fusions) had extremely poor expression or severe aggregation issues (Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.97844DS1). However, 2 peptides with the sequences QRNPRLRLIRRHPTLRIPPI and SAMFVPFDIAVGVRDGQQGLGGSRRKGARLREAISSYAE (referred to hereafter as QRN and SAM) were well expressed and had high monomeric content. Binding to either human (h) or murine (m) pIgR was then evaluated via ELISA (Figure 1). Cam-003–QRN was found to bind to m-pIgR with a half maximal effective concentration (EC50) of 0.50 μg/ml and to h-pIgR with an EC50 of 0.52 μg/ml. Cam-003–QRN binding exceeded that of human dIgA, a natural ligand for pIgR, which bound with an EC50 of 11.7 μg/ml for h-pIgR and 8.7 μg/ml for m-pIgR. Cam-003–SAM had only minimal binding to pIgR via ELISA and was not carried forward for further experiments. Figure 1 Cam-003 peptide fusions bind to human and murine pIgR. Binding of C-terminal peptide antibody fusions to pIgR was determined by ELISA. Cam-003 alone showed no binding to either human (A) or murine (B) pIgR at the highest concentration tested (200 μg/ml). Cam-003–QRN and its derivative Cam-003–KLKL had improved binding to pIgR compared with the natural pIgR ligand dimeric IgA, whereas another peptide fusion Cam-003–SAM exhibited poorer binding (n = 4). Data are representative of at least 2 independent experiments. Generation of the Cam-003–QRN variants. Cam-003–QRN bound effectively to both human and murine pIgR, yet mass spectrometric analysis of purified Cam-003–QRN revealed that protease cleavage occurred at 2 regions within the QRN peptide sequence (Supplemental Figure 1). The major species (species 1) observed was full length or missing the C-terminal isoleucine or the C-terminal dipeptide PI. An additional less abundant species observed was cleaved in the RLRL region midpeptide (species 2). Peak heights were used to estimate the abundance of the 2 species (Supplemental Figure 1). Analysis of 3 separate batches revealed QRN species 1 was ~70% abundant upon purification, whereas QRN species 2 was present at ~30% abundance. To increase the amount of species 1 QRN peptide, several mutants were generated in the RLRL sequence of the QRN peptide fusion (Supplemental Table 2). Of these, 1 mutant with lysines replacing 2 arginine residues in this sequence (referred to as KLKL) could be expressed consistently with high species 1 content (~85%) and maintained binding to h-pIgR and m-pIgR similarly to the parental QRN fusion (Figure 1). Cam-003–KLKL bound to m-pIgR with an EC50 of 0.43 μg/ml and to h-pIgR with an EC50 of 0.89 μg/ml via ELISA. Other mutations within the RLRL sequence of the QRN peptide either did not retain pIgR binding or had less full-length (species 1) heavy chains observed than the original QRN peptide. IgG peptide fusions transcytosis in pIgR-expressing cells. As the QRN C-terminal antibody fusion and engineered KLKL variant bound to the pIgR receptor, we next sought to determine whether these antibody fusions could be cargo for pIgR-mediated transcytosis. Stable human and murine pIgR expressing Madin-Darby canine kidney (MDCK) cells were generated to assess pIgR-mediated transcytosis (22). Cam-003 and Cam-003 peptide fusions were then evaluated in transwell assays. Antibodies were added in the bottom (basolateral side) chamber, and transcytosis was measured by quantifying antibody in the top (apical) chamber (Figure 2A). In either h-pIgR– or m-pIgR–expressing MDCK cells, Cam-003 levels in the apical chamber were at low levels, similar to untransfected MDCK cells (Figure 2B). After 24 hours, increased transcytosis was observed for both Cam-003–KLKL and Cam-003–QRN when compared with Cam-003 alone in wells with both h-pIgR– and m-pIgR–expressing MDCK cells (Figure 2B). Figure 2 Transcytosis of Cam-003 peptide fusions in pIgR-transfected MDCK cells. Antibodies were added to the bottom chamber (basolateral) of transwells containing either untransfected, h-pIgR–, or m-pIgR–transfected Madin-Darby canine kidney (MDCK) monolayers (A). At 24 hours, antibodies in the top chamber (apical) were quantified by ELISA. Cam-003 levels were similar in all 3 cell lines, whereas Cam-003–QRN and Cam-003–KLKL, as well as human dimeric IgA, had increased accumulation in the apical chamber (B). Data are representative of at least 2 independent experiments (n = 10 for Cam-003 antibodies, n = 6 for dIgA). Significance was determined using 2-way ANOVA (with Tukey’s post hoc test; ****P < 0.0001). pIgR-binding IgG fusion levels increased in BAL. We then determined how Cam-003–QRN and Cam-003–KLKL fusions would alter antibody localization to the lung lumen when administered i.v. to mice. Cam-003–QRN, Cam-003–KLKL, and Cam-003 IgG were dosed via tail-vein injection into mice, followed by collection of BAL fluid 48 hours after administration. Serum samples taken at 24 and 48 hours were also collected, and antibody levels were determined by biolayer interferometry (OCTET). Serum levels were similar between Cam-003 and the Cam-003 pIgR peptide fusions (Figure 3A). However, Cam-003–QRN and Cam-003–KLKL exhibited 2.7- and 3.9-fold higher IgG concentrations, respectively, in BAL fluid 48 hours after antibody administration when compared with Cam-003 (Figure 3B). Figure 3 Increased levels of Cam-003 variants in bronchoalveolar lavage and similar levels in serum. (A) Serum levels of Cam-003, Cam-003–QRN, and Cam-003–KLKL were quantified from BALB/c mice 24 and 48 hours after initial i.v. injection. Serum levels did not differ significantly at 24 or 48 hours. (B) Cam-003–QRN and Cam-003–KLKL levels in BAL (assessed at 48 hours) were elevated from those of Cam-003 alone (P = 0.195 and 0.023, respectively; 1-way ANOVA with Tukey’s post hoc test; *P < 0.05). Data are representative of at least 2 independent experiments; n = 4 per group. Assessing antibody fusions for OPK activity against P. aeruginosa. Prior to testing the pIgR-binding Cam-003 fusions in a P. aeruginosa infection model, we first assessed whether these antibodies maintain the ability to promote Fc-mediated phagocyte-dependent killing of P. aeruginosa. It has previously been shown that Cam-003 promotes OPK of P. aeruginosa and that this mechanism of action correlates with protective activity in vivo (15). Robust complement-dependent OPK of the P. aeruginosa strain PAO1 was observed with Cam-003 with EC50 values of 0.11 μg/ml (Figure 4A). Cam-003–QRN– and Cam-003–KLKL–mediated OPK was similar to Cam-003 alone (EC50 values 0.09 and 0.15 μg/ml, respectively), suggesting the C-terminal peptide fusions did not significantly impair OPK activity. Samples lacking antibody (media only) or with an isotype control IgG failed to elicit OPK activity against P. aeruginosa (Figure 4A). For this experiment, human serum (depleted of Pseudomonas-binding antibodies) was used as a complement source. OPK with an additional commonly used complement source (baby rabbit complement) was also evaluated (Supplemental Figure 3). Again, Cam-003, Cam-003–QRN, and Cam-003–KLKL displayed robust OPK activity, with the peptide fusions having slightly lower EC50 values than Cam-003. Figure 4 pIgR-binding Cam-003 fusions elicit opsonophagocytic killing and improved protection against lethal challenge in a P. aeruginosa acute pneumonia model. (A) Opsonophagocytosis assay with luminescent P. aeruginosa serogroup 05 strain PAO1 (PAO1.lux). OPK with Cam-003–QRN, Cam-003–KLKL, and Cam-003 are shown with the isotype control IgG R347. (B–D) Survival of BALB/c mice prophylactically immunized with an IgG isotype control R347, Cam-003, and either Cam-003–QRN (B) or Cam-003–KLKL (C and D) prior to i.n. infection with P. aeruginosa strain 6077. Results are represented as Kaplan-Meier survival curves; differences in survival were calculated by the log-rank test (Mantel-Cox). Data are representative of at least 2 independent experiments; n = 10 per group for survival experiments. (B) Cam-003 and Cam-003–QRN had significantly better protection than the isotype control at both doses tested (P < 0.0001 for both 5 and 10 mg/kg doses; 4.5 × 105 CFU inculcation). Cam-003–QRN survival was significantly improved compared with Cam-003, as well (P = 0.0014 for 5 mg/kg doses and P = 0.0098 for 10 mg/kg doses). (C) At 5 × 105 CFU, Both Cam-003 and Cam-003–KLKL were protective compared with R347 at both doses (P = 0.017, 2 mg/kg Cam-003; P = 0.0004, 6 mg/kg Cam-003; P < 0.0001, 2 and 6 mg/kg doses of Cam-003–KLKL). Cam-003–KLKL survival was superior to Cam-003 when comparing both the 2 mg/kg doses (P = 0.0042) and 6 mg/kg doses (P = 0.017). (D) At an 8 × 105 CFU inoculum dose, Cam-003 and Cam-003–KLKL survival was again enhanced compared with R347 (P < 0.0001, 2 mg/kg Cam-003; P = 0.0002, 6 mg/kg Cam-003; P < 0.0001, Cam-003–KLKL), with Cam-003–KLKL survival also enhanced compared with Cam-003 (P = 0.017, 6 mg/kg; not significant, 2 mg/kg). pIgR-binding peptide fusion mAbs exhibit enhanced protective activity in vivo. Given that Cam-003 pIgR fusion mAbs could still elicit OPK activity, we next sought to evaluate whether they provided improved protection in vivo in comparison with the parental Cam-003 mAb and a control IgG. The pIgR-binding peptide fusions, as well as Cam-003, were then tested for their ability to protect against lethal P. aeruginosa infection in a murine acute pneumonia model following prophylactic administration of the antibodies. A highly pathogenic strain of P. aeruginosa (strain 6077) was delivered i.n. 24 hours after i.v. administration of either Cam-003, Cam-003–QRN, or the isotype control antibody R347, and survival was monitored. In this initial experiment, both Cam-003–QRN and the parental Cam-003 mAbs at both concentrations exhibited significant enhanced survival when compared with the control IgG (Figure 4B). Moreover, Cam-003–QRN at both 10 and 5 mg/kg yielded enhanced protective activity when compared with the parental Cam-003 mAb at each antibody concentration (Figure 4B). We next sought to evaluate the activity of Cam-003–KLKL using a similar experimental design. In this experiment, both Cam-003–KLK–dosed groups (6 and 2 mg/kg) survived challenge (Figure 4C). This 100% protective effect for Cam-003–KLKL was a statistically significant when compared with both the isotype control and the parental Cam-003 molecule at both the 2 and 6 mg/kg dosage levels. A higher infectious inoculum, approximately 4-fold above the 100% lethal dose (LD100) for this strain (8 × 105 CFU/mouse), was then administered to assess whether the survival improvement over the parental Cam-003 afforded by Cam-003–KLKL would persist with greater lung burden. Cam-003 again had a significant protective effect compared with the isotype control at both dosage levels; however, all Cam-003–treated animals succumbed to infection within 50 hours (Figure 4D). Cam-003–KLKL–dosed animals again showed improved survival compared with both the isotype control and the parental molecule Cam-003. Even with an infectious inoculum at 4 times the LD100 for strain 6077, multiple animals within the Cam-003–KLKL groups survived the challenge until the end of the study, again demonstrating superiority to the parental molecule. Discussion The pIgR plays a key role in mucosal immunity by transporting large amounts of oligomeric IgA and IgM into the lumen of organs such as lungs and intestine. In addition to these endogenous pIgR ligands, IgG antibodies (23), Fabs (24–26), single-chain variable fragments (scFvs) (27, 28), camelid VHH domains (29), and phage-derived peptides (20, 21) have been generated over the last 2 decades by several laboratories to bind and become cargo for pIgR-mediated transport. Most of these engineered pIgR ligands show some level of transcytosis in cell monolayers, but few of these have been tested in vivo as to whether they can be transported to mucosal organs. In a notable exception, Fab domains targeting pIgR conjugated to polylysine and bound to condensed plasmid DNA were used to for gene delivery to the mouse lung lumen after i.v. administration (25). In that study, protein expression of the delivered gene was highly elevated in the lung lumen compared with the same complex with a nontargeting Fab. This unique proof-of-concept work showed for the first time to our knowledge that pIgR targeting can lead to accumulation of cargo in the lung lumen upon systemic administration. Our work herein expands on these results by using a human IgG antibody, Cam-003, as cargo to be transported to the lung lumen by high-affinity pIgR-binding peptides. Cam-003 targets the Psl exopolysaccharide of P. aeruginosa and has been shown to mediate protection in a murine model of acute pneumonia (15). We show that, by appending pIgR binding capabilities to Cam-003, we increase its levels in BAL fluid and that this enhanced accumulation correlates with improved protective activity when compared with the parental IgG. This result underscores the potential for this approach to improve the efficacy of antibodies with targets in the lung lumen. In this study, we screened multiple peptides reported to bind and be transported by pIgR for their ability to be expressed as IgG fusions and maintain pIgR binding. Only the QRN peptide met these criteria. The KLKL peptide offered a modest improvement in full-length peptide content compared with QRN. Ultimately, further peptide engineering will be needed to both eliminate protease susceptibility and identify optimal attachment sites to IgG for mitigating any potential decreases in FcγR or C1q binding. The binding of peptide-IgG fusions to FcγR or C1q was not assessed because OPK activity was minimally affected by the addition of peptides; however, the potential exists that effector function could be impaired by attaching peptides or other fusions to the Fc. As an alternative to peptide engineering, we predict a similar result could be achieved with bispecific antibodies (with 1 or more pIgR-targeting arms) rather than peptides. A dIgA format (a natural pIgR ligand) has recently been used to deliver antibody to mouse kidney cysts, tissue that is relatively inaccessible to IgG antibodies (30). We predict a similar result could be achieved using our approach to endowing existing IgG antibodies with the ability to bind and be transported by pIgR. An IgG-based approach could be advantageous compared with dIgA due to IgG’s favorable pharmacokinetics, relative ease of manufacture, and homogeneity. Indeed, serum levels of Cam-003–QRN and Cam-003–KLKL at 24 and 48 hours were similar to those of the parental IgG. dIgA is known to have a much quicker serum clearance (~4–5 times faster) (31). As our study and another (25) have shown, systemic administration of pIgR-targeting antibodies or fragments increases accumulation in lungs. In this study, we did not assess accumulation in other mucosal organs such as the kidneys or intestines. Results with dIgA accumulation in kidney cysts (30) confirm pIgR-binding Ig can indeed accumulate in organs other than the lungs. Further studies will be necessary to determine where pIgR-binding Ig accumulate upon various routes of administration (ROA) and whether a specific ROA can cause more accumulation in specific mucosal tissues versus others. Nevertheless, the ability to access mucosal surfaces that have previously been poorly accessible to IgG therapeutics presents an opportunity for enhancing efficacy to both microbial and endogenous targets within these tissues. Methods Cloning. C-terminal peptide fusions were generated using overlapping PCR with synthetic oligonucleotides synthesized at Integrated DNA Technologies. PCR fragments were cloned into a MedImmune proprietary mammalian expression vector (32). Standard molecular biology methods were used for cloning, vectors preparation, and DNA sequencing. E. coli One Shot Stbl3 chemically competent cells, used for DNA amplification, were purchased from Thermo Fisher Scientific. Expression and purification. Antibodies were expressed as previously described (33). Briefly, expression vectors expressing both antibody light and heavy chains were transfected in CHO-G22 cells. CHO-G22 cells were cultured with 25 μM l-methionine sulfoximine and 100 μg/ml hygromycin in MedImmune’s proprietary CHO-V2 medium at 37°C, 5% CO2, and 80% humidity. Twenty-four hours prior to transfection, CHO-G22 cells were diluted to 1 × 106 cells/ml in CHO-V2 medium without hygromycin and l-methionine sulfoximine and grown overnight. mAb expression vector (500 μg) was diluted into 7.5 ml of 150 mM sodium chloride, and 2.5 ml of 1 mg/ml PEI MAX (Polysciences) was mixed with 5 ml of the 150 mM sodium chloride solution (VWR). The DNA and PEI-max solutions were combined and incubated for 1 minute at room temperature before being added to 500 ml of 2 × 106 CHO-G22 cells. The transfected cells were grown for 24 hours as described above. Thereafter, the temperature was changed to 34°C and supplemented with 500 ml of CHO-V2 medium. Culture medium was collected 10 days after transfection. Antibody variants were purified using standard protein A affinity chromatography and were subsequently buffer exchanged using dialysis in PBS (pH 7.2). Monomeric content of the antibodies and antibody fusions were analyzed using analytical size-exclusion chromatography (SEC-HPLC). Antibodies having an initial monomer content below 98% had aggregate removed by preparative SEC-HPLC prior to testing (Supplemental Figure 2). ELISA binding to pIgR. Human or murine pIgR extracellular domain (R&D Systems) was coated on 96-well maxisorp plates (Nunc) overnight at 4°C (2 μg/ml in PBS). Plates were then blocked with 2% BSA in PBS for 2 hours at room temperature. After washing, titrated antibodies or antibody fusions were added and allowed to incubate for 1 hour. After 3 washes in PBS, peroxidase-conjugated anti–human Fd (Southern Biotech, catalog 2046-05) was used to as a detection reagent. The wells were washed 3 times, and TMB substrate solution was added. The reaction was stopped with 2 N H2SO4, and the absorbance at 450 nm was measured. Transcytosis assay. MDCK (purchased from ATCC) transcytosis experiments were conducted similarly to Jerdeva et. al (34). Stably transfected MDCK cells expressing either murine or human full-length pIgR were plated in transwell plates with at 500,000 cells/well with MEM + 10% or FBS + 1% penicillin-streptomycin. MDCK pIgR cells were generated in house using a lentiviral vector and confirmed to have pIgR expression. Media (1 ml) was added on the top (apical) side; 0.5 ml of media was added on the bottom (basolateral) side. Media was changed every 48 hours prior to beginning transcytosis experiment. Cells were used for experiments on the fourth or fifth day after plating, after confluent monolayers had formed. Antibody (20 μg) was added to the bottom chamber, and media was collected from the top chamber; antibody amount was assessed by OCTET or quantitative ELISA. BAL and serum collection and quantification. BALB/c mice (6–8 weeks old; Envigo) were given a bolus i.v. dose of 2.5 mg/kg antibody. Four mice were used per antibody. Blood samples were obtained from the retro-orbital plexus using capillary pipettes at 24 hours and via cardiac puncture at 48 hours. BAL was taken at 48 hours by washing the lung lumen with 1 ml of PBS 3× and collecting. Biolayer interferometry (OCTET; FortéBio Inc.) was used to monitor the serum or BAL concentrations of the tested antibodies. Briefly, samples or buffer were dispensed into 384-well microtiter plates (FortéBio Inc.) at a volume of 50 μl per well. Operating temperature was maintained at 30°C. Anti–human Fab–coated biosensor tips (FortéBio Inc.) were prewetted with PBS. Standard curves were generated for each antibody variant, generated via OCTET analysis software. Sample concentrations were generated automatically based on the standard curve via the OCTET User Software (version 3.1) and was subsequently analyzed via Prism (GraphPad Software). OPK assay. Assays were performed as previously described, with some modifications (15). OPK assays were performed in a 96-well plate format. P. aeruginosa strain PA01-lux (expressing luciferase) was constructed as previously reported (35) and grown to mid log-phase in LB media, and cultures were diluted to 2 × 106 cells/ml. Bacteria (25 μl) were then combined with an equal volume of 10% baby rabbit serum; differentiated HL-60 cells (2 × 107 cells/ml) as the polymorphonuclear leukocyte source; and titrated mAb. After 2-hour shaking at 37°C, relative luciferase units (RLUs) for each well were determined using an Envision Multilabel plate reader (PerkinElmer). The percentage of killing was determined by comparing RLUs derived from assays lacking mAb (no OPK) to RLUs obtained from assays with anti-Psl mAbs or the control R347 mAb (generated in-house). For OPK assays using human sera as a complement source, human serum was first adsorbed against an isogenic Psl-deficient mutant strain (PAO1ΔpslA) (15) and filter sterilized (0.2 μm). Adsorbed sera was then used in place of rabbit sera in the OPK assay described above. HL-60 cells were purchased from ATCC. In vivo P. aeruginosa model. Studies were performed essentially as described previously (15, 36) with some modifications. Guidelines for humane end points were strictly followed. Antibodies were administered 24 hours before infection with P. aeruginosa strain 6077 in the acute pneumonia model. BALB/c mice (Envigo) were infected with 6077 suspended in a 0.05-ml inoculum. Strain 6077 was a gift from Joanna Goldberg (Emory University, Atlanta, Georgia, USA). Statistics. Data were analyzed using 1-way ANOVA with Tukey’s post hoc test or 2-way ANOVA with Tukey’s post hoc test. For survival studies, data are presented as Kaplan-Meier survival curves and were analyzed by the log-rank test. All statistical analyses were performed using GraphPad Prism version 7 software. Study approval. All animal studies were approved by the MedImmune IACUC and were conducted in an Association for Assessment and Accreditation of Laboratory Animal Care–accredited facility in compliance with US regulations governing the housing and use of animals. Donor serum was obtained using a MedImmune approved IRB protocol (IRB Pro00004341). Author contributions MJB, AD, and RG designed experiments, performed experiments, analyzed data, and wrote the manuscript. GMM and NB performed experiments. MPM designed experiments. NB, MJB, KJL, and SSP produced the antibodies or cell lines. ASB performed mass spectrophotometric analysis. PT, HW, and WFD wrote the manuscript. Supplemental material View Supplemental data Acknowledgments Research was supported by MedImmune, a member of the AstraZeneca group. Footnotes Conflict of interest: All authors are employees of, or have received funding from, MedImmune, a member of the AstraZeneca group. Reference information: JCI Insight. 2018;3(12):e97844. https://doi.org/10.1172/jci.insight.97844. References Shadman KA, Wald ER. A review of palivizumab and emerging therapies for respiratory syncytial virus. Expert Opin Biol Ther. 2011;11(11):1455–1467. View this article via: PubMed CrossRef Google Scholar DiGiandomenico A, et al. A multifunctional bispecific antibody protects against Pseudomonas aeruginosa. Sci Transl Med. 2014;6(262):262ra155. View this article via: PubMed CrossRef Google Scholar Hua L, et al. 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Gilbert C FAURE
January 17, 2018 10:35 AM
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The human penis is a main portal of entry for numerous pathogens, and vaccines able to control resulting infections locally are highly desirable. However, in contrast to the gastrointestinal or vaginal mucosa, the penile immune system and mechanisms inducing a penile immune response remain elusive. In this descriptive study, using multiparametric flow cytometry, and immunohistochemistry, we characterized mucosal immune cells such as B, T and NK cells from the urethra, fossa and glans of human adult penile tissues. We show that memory B lymphocytes and CD138+ plasma cells are detected in all penile compartments. CD4+ and CD8+ T lymphocytes reside in the epithelium and lamina propria of the penile regions and have mostly a resting memory phenotype. All penile regions contain CD56dim NK cells surface-expressing the natural cytotoxicity-receptor NKp44 and the antibody-dependent cell-cytotoxicity (ADCC) receptor CD16. These cells are also able to spontaneously secrete pro- and anti-inflammatory cytokines as IL-17 and IL-22. Finally, CCR10 is the main homing receptor detected in these penile cells although, together with CCR3, CCR6, CCR9, their expression level differ between penile compartments. Unlike antigen-presenting cells which type differ between penile regions as we reported earlier, urethral, fossa and glans content in immune B, T and NK cells is comparable. However, median values per each analysis suggest that the glans, containing higher number and more activated NK cells together with higher number of terminally differentiate effector CD8+ T cells, is a superior effector site than the urethra and the fossa. Thus, the human penis is an immunologically active tissue containing the cellular machinery required to induce and produce a specific and effective response against mucosal pathogen. It can be considered as a classic mucosal effector site and this must be taken into account for the elaboration of efficient strategies, including vaccines, against sexual transmitted infections.
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Scooped by
Gilbert C FAURE
May 23, 2017 9:42 AM
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Interleukin-22 (IL-22) acts protectively and harmfully on intestinal tissue depending on the situation; therefore, IL-22 signaling needs to be tightly regulated. IL-22 binding protein (IL-22BP) binds IL-22 to inhibit IL-22 signaling. It is expressed in intestinal and lymphoid tissues, although its precise distribution and roles have remained unclear. In this study, we show that IL-22BP is highly expressed by CD11b+CD8α− dendritic cells in the subepithelial dome region of Peyer’s patches (PPs). We found that IL-22BP blocks IL-22 signaling in the follicle-associated epithelium (FAE) covering PPs, indicating that IL-22BP plays a role in regulating the characteristics of the FAE. As expected, FAE of IL-22BP–deficient ( Il22ra2− /−) mice exhibited altered properties such as the enhanced expression of mucus and antimicrobial proteins as well as prominent fucosylation, which are normally suppressed in FAE. Additionally, Il22ra2− /− mice exhibited the decreased uptake of bacterial antigens into PPs without affecting M cell function. Our present study thus demonstrates that IL-22BP promotes bacterial uptake into PPs by influencing FAE gene expression and function.
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Scooped by
Gilbert C FAURE
October 24, 2016 2:52 PM
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Intestinal inflammation can impair mucosal healing, thereby establishing a vicious cycle leading to chronic inflammatory bowel disease (IBD). However, the signaling networks driving chronic inflammation remain unclear. Here we report that CD4+ T cells isolated from patients with IBD produce high levels of interleukin-22 binding protein (IL-22BP), the endogenous inhibitor of the tissue-protective cytokine IL-22. Using mouse models, we demonstrate that IBD development requires T cell–derived IL-22BP. Lastly, intestinal CD4+ T cells isolated from IBD patients responsive to treatment with antibodies against tumor necrosis factor–α (anti–TNF-α), the most effective known IBD therapy, exhibited reduced amounts of IL-22BP expression but still expressed IL-22. Our findings suggest that anti–TNF-α therapy may act at least in part by suppressing IL-22BP and point toward a more specific potential therapy for IBD.
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Scooped by
Gilbert C FAURE
May 18, 2016 9:20 AM
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Bruno Lamas, Mathias L Richard, Valentin Leducq, Hang-Phuong Pham, Marie-Laure Michel, Gregory Da Costa, Chantal Bridonneau, Sarah Jegou, Thomas W Hoffmann, Jane M Natividad, Loic Brot, Soraya Taleb, Aurélie Couturier-Maillard, Isabelle Nion-Larmurier, Fatiha Merabtene, Philippe Seksik, Anne Bourrier, Jacques Cosnes, Bernhard Ryffel, Laurent Beaugerie, Jean-Marie Launay, Philippe Langella, Ramnik J Xavier & Harry Sokol
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Suggested by
Société Francaise d'Immunologie
October 1, 2015 3:18 PM
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Infect Immun. 2015 Aug;83(8):3257-67. doi: 10.1128/IAI.00670-15. Research Support, Non-U.S. Gov't
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Suggested by
Société Francaise d'Immunologie
January 21, 2019 1:44 PM
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Background It is hypothesized that uncontrolled inflammation is responsible for many of the manifestations and symptoms of chronic rhinosinusitis (CRS). Although earlier work has demonstrated an association between olfactory loss and mucus cytokines, the impact on other symptoms is unknown. In this study we investigated the relationship between cytokines, inflammatory cell counts, and patient‐reported outcomes measures to better understand how the inflammatory microenvironment correlates with CRS symptomatology. Methods The 22‐item Sino‐Nasal Outcome Test (SNOT‐22) and 8‐item Short Form Health Survey (SF‐8) were administered to 76 patients undergoing endoscopic sinus surgery for CRS. Mucus was collected intraoperatively from the middle meatus and tested for 17 cytokines using a multiplex flow cytometric bead assay. Eosinophil/neutrophil counts were obtained from histopathologic slide review. Spearman correlations between cytokines, cell counts, and quality‐of‐life subdomain scores were assessed without multiple comparisons correction due to the small sample size. Results Interleukin‐4 (IL‐4) correlated significantly with the Rhinologic domain (Rs = 0.25, p = 0.03), whereas eosinophil and neutrophil counts were inversely correlated with the Extranasal Rhinologic domain (Rs = −0.32, p = 0.01; and Rs = −0.27, p = 0.03). Subgroup analysis for nasal polyposis (CRSwNP) showed significant correlations between IL‐6 and Total SF‐8 (Rs = 0.35, p = 0.02), General Health (Rs = 0.34, p = 0.03), and Emotional (Rs = 0.47, p = 0.002) scores. In patients without polyps (CRSsNP), IL‐21 correlated positively with Extranasal Rhinologic Symptoms domain (Rs = 0.41, p = 0.01). Conclusion This pilot study identifies possible pairwise correlations between mucus cytokine levels and baseline quality‐of‐life measures that need confirmation in larger, targeted studies. Due to the exploratory methodology, positive results may be spurious and should only be used as a starting point for future confirmatory work.
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Scooped by
Gilbert C FAURE
November 25, 2018 1:21 PM
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Abstract Mucosa‐associated invariant T (MAIT) cells are unconventional T lymphocytes defined by their innate‐like characteristics and broad antimicrobial responsiveness. Whether MAIT cells are part of the tissue‐resident defense in the oral mucosal barrier is unknown. Here, we found MAIT cells present in the buccal mucosa, with a tendency to cluster near the basement membrane, and located in both epithelium and the underlying connective tissue. Overall MAIT cell levels were similar in the mucosa compared to peripheral blood, in contrast to conventional T cells that showed an altered representation of CD4+ and CD8+ subsets. The major mucosal MAIT cell subset displayed a tissue‐resident and activated profile with high expression of CD69, CD103, HLA‐DR, and PD‐1, as well as a skewed subset distribution with higher representation of CD4–/CD8– double‐negative cells and CD8αα+ cells. Interestingly, tissue‐resident MAIT cells had a specialized polyfunctional response profile with higher IL‐17 levels, as assessed by polyclonal stimulus and compared to tissue nonresident and circulating populations. Furthermore, resident buccal MAIT cells were low in perforin. Together, these data indicate that MAIT cells form a part of the oral mucosal T cell compartment, where they exhibit a tissue‐resident‐activated profile biased toward IL‐17 production. Introduction Mucosa‐associated invariant T (MAIT) cells are nonclassical innate‐like T cells that recognize microbial antigens presented by the MHC‐Ib‐related protein 1 (MR1) 1, 2. MR1 displays an extraordinary level of evolutionary conservation among mammals 2-4, and was shown to present microbial vitamin B2 (riboflavin) metabolites from a wide range of microbes that carry the riboflavin biosynthesis pathway 5, 6. MAIT cells express a semi‐invariant T cell receptor (TCR), including the Vα7.2 segment coupled with Jα33, Jα12, or Jα20, and limited TCR β‐chain diversity 7, 8. This TCR repertoire endows MAIT cells with the capacity to respond to the MR1‐restricted riboflavin derivatives produced by diverse microbes 9, 10. MAIT cells respond to antigenic stimulus with an innate‐like speed and produce proinflammatory cytokines including TNF, IFN‐γ, and IL‐17 9, 11-14. They can furthermore kill cells infected by microbes expressing the riboflavin pathway 15, 16 and inhibit intracellular microbial growth 17. Human MAIT cells are also defined by their high expression of CD161, the IL‐18 receptor α subunit (IL‐18Rα), and the transcription factor ZBTB16 18, also known as promyelocytic leukemia zinc finger protein (PLZF) 9, 19. The majority of MAIT cells are CD8+, with some being CD4–/CD8– double‐negative (DN), and a minor CD4+ population 9, 11, 12, 19. Human MAIT cells acquire innate‐like antimicrobial activity in the fetal intestinal mucosa prenatally, prior to the establishment of the commensal microflora 14. In adults, MAIT cells are highly abundant in mucosal tissues, liver, and peripheral blood 1, 2, 20-22. Studies of the murine oral immune system revealed diverse populations of DCs 23, 24, and provided insight into oral T‐cell function 25, but the immunology of the human oral mucosa remains relatively little studied. However, Dutzan et al. recently performed a broad characterization of the immune cell network at the gingival interface and identified T cells as the dominant immune cell population in both the buccal and gingival mucosa 26. CD4+ T cells, mainly of the CD45RO+ "memory" phenotype, were found to be the largest subset at around half of CD3+ cells, whereas smaller subsets of CD8+ and γδ T cells were also present 26. The same study also identified tissue‐resident CD4+ T cells as major producers of IL‐17 in periodontitis. IL‐17 is a cytokine central to the regulation of immune activity at mucosal surfaces 27, 28. Although IL‐17 is implicated in a variety of functions, its role in the regulation of mucosal immunity hinges on three core effects: maintenance of mucosal integrity via regulation of tight junction proteins, induction of antimicrobial molecule production by epithelial cells, and recruitment of neutrophils to sites of infection. Given the capacity of MAIT cells to recognize and respond to several commensal and disease causing microbes occurring in the oral cavity, and the ability of these cells to locate to mucosal sites, one can hypothesize a role for MAIT cells in the oral mucosal barrier. However, the immunobiology of MAIT cells at this mucosal site has to date not been explored. In the present study, we therefore investigated the presence, location, characteristics, and function of MAIT cells in the human buccal mucosa. The findings demonstrate that MAIT cells are part of the healthy buccal mucosal immune defense with specialized tissue‐resident and nonresident subpopulations exhibiting distinct functional profiles, where in particular, the CD69+CD103+ MAIT cell population show strong IL‐17 production. We discuss these findings in the context of contemporary knowledge of immune homeostasis and defense at this important barrier site. Results Identification of MAIT cells in the buccal mucosa Given the broad antimicrobial reactivity of MAIT cells, we were interested in investigating the potential role of these cells in oral mucosa, a site continuously exposed to a broad array of microbial stimuli. Buccal biopsies and matched peripheral blood samples were collected from healthy donors (Supporting Information Table 1), and cells isolated after tissue processing were analyzed by flow cytometry. All subjects were examined for their oral health and showed no oral mucosal disease, active dental caries, infection, or periodontitis. Using antibody combinations allowing identification of MAIT cells in blood, buccal MAIT cells were defined as CD45+ CD3+ CD161hi Vα7.2+ cells (Fig. 1A). To ensure that cells defined by this gating strategy were bona fide MAIT cells, their MR1 restriction was confirmed by staining with the MR1 5‐(2‐oxopropylideneamino)‐6‐D‐ribitylaminouracil (5‐OP‐RU) tetramer (Fig. 1B). The percentage of MAIT cells in the mucosa ranged between 0.1 and 7% of total T cells (Fig. 1C). Overall, these levels were not significantly different from those in matched blood, although in any given individual, the levels seen at the two sites were often rather divergent. Interestingly, major conventional T‐cell subsets were present in the buccal mucosa at frequencies different from those in the blood. Levels of CD4+ T cells were lower than in blood, whereas CD8+ T cells and CD4–CD8– T cells were enriched in buccal mucosa as compared to blood (Fig. 1C). These data demonstrate that MAIT cells are part of the buccal mucosa T‐cell compartment. Detection of buccal mucosal MAIT cells in situ To determine MAIT cell location within the buccal mucosa, we performed in situ staining for Vα7.2 and IL‐18Rα in oral mucosal sections (Fig. 1D). In mucosa, staining for IL‐18Rα can be used in lieu of CD161, as we have previously shown for genital mucosa 22. Using the Vα7.2+ IL‐18Rα+ definition, MAIT cells were readily identified in buccal mucosal sections, and they tended to locate close to the basement membrane (Fig. 1D). MAIT cells were present in the epithelial layer, just above the basal membrane (distance from basal membrane: median = 14.6 μm; range = 1.0–75.9 μm), as well as in the underlying connective tissue, just beneath the basal membrane (median = 20.7 μm; range = 2.8–292.2 μm). Non‐MAIT T cells, as well as MR1‐expressing HLA‐DR+ antigen‐presenting cells, were also found in buccal mucosa as determined by immunofluorescence staining (Fig. 1E and F). MAIT cell location around the basement membrane is consistent with a possible role as innate‐like T cell sentinels to detect microbial epithelial barrier breach. Altered subset distribution and Jα‐TCR usage in mucosal MAIT cells In peripheral blood, MAIT cells are predominantly CD8+, with some CD4–CD8– cells and a very small CD4+ subpopulation. In the buccal mucosa, MAIT cells were enriched in CD4–CD8– and CD4+ subsets, and had significantly lower levels of the CD8+ subset (Fig. 2A). Within the CD8+ subset, similar to blood MAIT cells, the mucosal MAIT cells exhibited an increased frequency of CD8αα+ cells compared to non‐MAIT T cells (Fig. 2B and C). Notably, MAIT cells represented almost half of all CD8αα+ T cells in the buccal mucosa, with significant donor variability (Fig. 2D). The distribution of Jα‐TCR usage within the MAIT cell populations in the buccal mucosa and blood was compared using quantitative real‐time PCR (qRT‐PCR; Fig. 2E). We quantified the relative expression of three Jα previously shown to be represented within the MAIT cell TCR repertoire, the Jα12, Jα20, and Jα33 8, 29, 30. As expected, blood MAIT cells displayed a consistent pattern with dominant Jα33 usage, with smaller Jα20 and Jα12 usage. However, in matched mucosa, the pattern was more diverse, with different Jα segments dominating in different donors. Together, these data support a model of compartmentalization where the subset representation and TCR‐Jα usage in buccal MAIT cell population are partly different that of the circulating MAIT cells found in blood. MAIT cells in buccal mucosa express an activated perforinlow phenotype To assess the phenotypic characteristics of the buccal MAIT cells in more detail, we next stained isolated mucosal cells with markers of activation, CD38 and HLA‐DR (Fig. 3A). The staining pattern revealed the presence of an activated HLA‐DR+CD38+ MAIT cell population in buccal mucosa (Fig. 3B). Compared to their blood counterparts, the mucosal MAIT cells expressed higher levels of HLA‐DR, whereas CD38 levels appear to be slightly lower (Fig. 3C). In addition, expression of PD‐1 was common in mucosal MAIT cells, whereas PD‐1 was less expressed in peripheral blood MAIT cells (Fig. 3C). To investigate the phenotype of MAIT cells in more detail, paired blood and mucosal cell samples were stained intracellularly for the expression of the master transcription factor PLZF, as well as the cytolytic effector molecules perforin and granulysin (Fig. 3D). Perforin levels were mostly lower in the buccal MAIT cells than in their blood counterparts (Fig. 3E), whereas expression levels of PLZF and granulysin were similar in both compartments. These findings suggest that MAIT cells in the buccal mucosa are highly activated cells with significant expression of the checkpoint inhibition receptor PD‐1, and display a reduced perforin content as compared to circulating MAIT cells. Characterization of resident and nonresident MAIT cells in the buccal mucosa We next investigated the MAIT cell expression of receptors associated with tissue residency in the mucosa. Resident T cells can be distinguished by coexpression of CD69 and CD103 (αE integrin) in a range of tissues 31-35, including intestinal mucosa 36. Flow cytometric assessment of CD69 and CD103 expression revealed the existence of a major CD69+CD103+ tissue‐resident MAIT cell population in the buccal mucosa (Fig. 4A). However, a minority of MAIT cells were negative for CD69 and CD103, consistent with a tissue nonresident or "passing through" phenotype (Fig. 4A). Compared to peripheral blood MAIT cells, the buccal mucosal MAIT cell population was highly enriched in CD69 and CD103 expression, and CD69 expression was mostly seen in the CD103+ population (Fig. 4B). As the CD69 expression formed a continuum including dim cells of both CD103+ and CD103– character, we compared the four MAIT cell populations defined by CD69 and CD103 with regard to CD4+ and CD8+ expression. CD103+ MAIT cells were mainly CD8+ with a minority CD4–CD8– cells, whereas CD103– MAIT cells had a distinct opposite pattern with a majority CD4–CD8– character (Fig. 4C and D). CD69 expression did not significantly influence this pattern (Fig. 4C). In addition, CD103+ MAIT cells were more activated than their CD103– counterparts, as evidenced by higher expression of HLA‐DR and CD38 (Fig. 4E). In contrast, the CD103+ subpopulation expressed lower levels of the cytolytic effector molecule perforin, whereas PLZF did not vary depending on CD103 (Fig. 4F). These results indicate the existence of two distinct buccal MAIT cell subpopulations where one express the CD103 marker of tissue residency and one lacks CD103 consistent with a nonresident character. Distinct polyfunctional responses of mucosal resident, nonresident, and circulating MAIT cells To investigate the functional profile of MAIT cells in buccal mucosa in comparison with peripheral blood, isolated lymphocytes from the two tissues were activated with PMA/ionomycin and their repertoire of functions evaluated by flow cytometry staining for TNF, IFN‐γ, IL‐2, IL‐17, and granzyme B (Fig. 5A). Overall, both blood and mucosal MAIT cells displayed detectable production of all these effector functions, with some notable tissue‐dependent differences. Peripheral blood MAIT cells produced TNF and IFN‐γ more strongly than their mucosal counterparts, whereas IL‐2 and granzyme B were similar (Fig. 5A and B). In contrast, IL‐17 production was very low in blood MAIT cells, with the exception of one outlier, while this cytokine was clearly more highly expressed in the buccal MAIT cells (Fig. 5A and B). In the mucosal tissue, the resident CD103+ subset and the CD103– nonresident subset were largely similar in their response patterns with two notable exceptions. IL‐17 in particular, and to some extent granzyme B expression, were significantly higher in the CD103+ MAIT cell subset. To understand the functional specialization of mucosal resident, mucosal nonresident, and circulating MAIT cells in more detail, we analyzed the polyfunctional response profiles of these subsets. First, we determined the percentages of MAIT cells in the three locations that responded with at least one of the five functions measured (Fig. 5C). For all three sites, the vast majority of MAIT cells expressed at least one function. However, the mucosal MAIT cells displayed somewhat lower responsiveness, where in particular, the CD103– MAIT cells were less responsive. When the overall polyfunctionality was analyzed, the ability to express 1, 2, 3, 4, or 5 functions was fairly similar between the different tissue locations, although the CD103+ resident MAIT cells tended to be more 4‐ or 5‐functional (Fig. 5D). Finally, we analyzed the data by Boolean gating to assess which specific polyfunctional profiles were expressed by peripheral blood, CD103+ mucosal resident, and CD103– nonresident MAIT cells (Fig. 5E; Supporting Information Table 2). This analysis brought forward the pattern that peripheral blood MAIT cells were focused primarily on TNF production, either alone or in combinations with IFN‐γ and IL‐2. The mucosal CD103+ resident MAIT cells instead primarily focused on IL‐17 production either alone or in combinations with TNF or IL‐2. The CD103– nonresident MAIT cells had a functional profile intermediate between the circulating and resident populations, and were mostly expressing TNF with or without IL‐2, and less IL‐17. Altogether, these findings indicate that the mucosal resident, the mucosal nonresident, and the circulating MAIT cells deploy different effector cytokine response profiles. Discussion Tissue‐resident immune cell populations are increasingly recognized for their importance in defense against invading pathogens. The oral mucosa is continuously exposed to a range of antigens derived from food, microbiota, and pathogens. To maintain barrier immune defenses at this site, while not reacting against nonpathogenic encounters, is a considerable challenge. Recent studies have started to address this research question 37, 38, but no studies to date have addressed the potential role of the MR1‐restricted MAIT cell population in oral mucosa. Here, we observe that MAIT cells are dispersed throughout the buccal mucosa with a preferential location close to the basement membrane. The buccal MAIT cells are biased toward a CD4–/CD8– DN profile, and the CD8+ subset is primarily CD8αα and make up a significant proportion of all CD8αα T cells in the mucosa. The MAIT cell population in this mucosal site is composed of distinct CD69+CD103+ intraepithelial resident and CD69–CD103– nonresident subsets. The CD103+ subset is enriched in CD8+ MAIT cells, is more activated, and has lower cytolytic potential. Finally, the buccal MAIT cells show a distinct functional profile with enhanced IL‐17 production and less TNF and IFN‐γ, as compared to their peripheral blood counterparts, and this pattern was particularly pronounced for the CD103+ resident MAIT cells. The MR1‐presented riboflavin metabolite antigens recognized by MAIT cells are conserved among many prokaryotic and eukaryotic microbes relevant for mucosal health. Thus, MAIT cells may play a unique role in the oral mucosa with broad innate‐like recognition of such microbes in a manner that does not require the kind of priming which conventional adaptive T‐cell responses do. It is interesting that the MAIT cells to at least some extent locate around the basement membrane, where they may function as innate‐like T‐cell sentinels to detect microbial epithelial barrier breach. Around the similar location, MR1+HLA–DR+ cells are residing and those may be able to present riboflavin metabolite antigens from invading microbes. Together, MAIT cells and MR1+ antigen presenting cells may form a rapid innate response immune unit at the mucosal barrier, capable of responding to pathogens to which the host has no preexisting adaptive immunity. The CD103+CD69+ mucosal‐resident MAIT cell population is fairly strongly biased toward IL‐17 production, with less TNF and IFN‐γ expression, as compared to the CD103– MAIT cell subpopulation. Resident MAIT cell recognition of an invading microbial pathogen may thus setoff an IL‐17‐mediated inflammatory response with induction of antimicrobial peptides in epithelium and recruitment of neutrophils. Such a pattern would be reminiscent to the situation described for chronic severe periodontitis by Dutzan et al. 26, where IL‐17 produced by presumably adaptive Th17 cells was associated with increased gingival tissue infiltration of neutrophils. Given their innate‐like response characteristics, MAIT cells may be among the first immune cells to detect microbial infiltration and respond with IL‐17 release. Here, it is interesting to note that IL‐17 has emerged as an important mediator and amplifier of immunity against Candida albicans 38. The dimorphic fungus C. albicans expresses the riboflavin biosynthesis pathway and is recognized by MAIT cells in an MR1‐restricted manner 10. Many cells respond to IL‐17 by upregulation of proinflammatory cytokines, such as IL‐6, and chemokines for recruitment of neutrophils including CXCL1, CXCL2, and CXCL5 39. In addition, IL‐17 stimulates production of β‐defensins in epithelial cells 40. MAIT cells are thus well located to initiate mucosal immune responses in oropharyngeal candidiasis. Peripheral blood MAIT cells are predominantly CD8+ with a minority CD4–CD8– subset. This pattern is reversed in buccal mucosa, such that the CD4–CD8– MAIT cells are more numerous. It is however interesting to note that the CD8+ MAIT subset in buccal mucosa is primarily CD8αα, and that this subset makeup almost half of all CD8αα T cells in the oral mucosa. These CD8αα MAIT cells bear resemblance to the intestinal mucosal CD8αα intraepithelial lymphocytes (IELs) that have been extensively characterized in murine models, but may be less frequent in humans 41, 42. The intestinal IELs of mice are a mix of TCRγδ T cells and TCRαβ T cells with diverse specificities, and the representation of MAIT cells among these IELs in different sites is to our knowledge largely unknown. Our data indicate that the CD103+ MAIT cell population is mostly, but not exclusively, CD8+ and composed of both CD8αα and CD8αβ cells. These findings together suggest that MAIT cells makeup a significant part of the human buccal IEL‐like population. The human oral mucosal barrier retains a commensal bacterial microbiota that is both varied and unique among other sites 43, 44, dominated by the genera Streptococcus, Haemophilus, Prevotella, and Veillonella. In addition to bacteria, the oral mucosal barrier is home to many species of fungi including C. albicans 45. The oral immune system thus has to manage and tolerate a diverse commensal microbiome, and at the same time guard against conditions arising either from dysfunction of normal oral homeostasis or caused by pathogens normally not present in the oral cavity. T cells are believed to play a role in multiple oral mucosa pathologies including aphthous stomatitis, oral leukoplakia, oral reticular or ulcerative lichen planus, celiac disease, and oral psoriasis 46, 47. Whether MAIT cells have a role in any such conditions in humans remains to be explored. In summary, we have shown that MAIT cell populations with resident and nonresident characteristics are part of the buccal mucosal immune system in healthy donors and that they have unique functional profiles. Future studies should aim to investigate how these populations respond to commensal and pathogenic microbes, and how they are affected in different disease conditions. Materials and methods Tissue donor recruitment and sample collection A total of 94 volunteers were recruited in two healthy donor groups A and B (Supporting Information Table 1). Inclusion criteria for both groups were: 20–50 years of age, HIV‐negative, non‐smoking, no antibiotics in the last 3 months, and not pregnant. Ethical permission was obtained from the Regional Ethical Review Board in Stockholm in accordance with the Declaration of Helsinki. All participants gave written informed consent. The oral health of all subjects was evaluated using standard dental examination procedures, including inspection of oral mucosa, teeth, and surrounding soft tissues, to ensure the donors had no visible mucosal lesions, no signs of gingivitis, active dental caries, or periodontitis. All donors were instructed to abstain from food or drink for 1 h before tissue collection. Oral mucosal tissue samples and matched peripheral blood samples were collected from two sets of healthy donors. Donor group A was recruited from the general population. A matched blood sample of 20–30 mL venous blood was taken from each participant on the day of the procedure, prior to the oral sample collection. The blood was stored in heparin tubes at room temperature until analysis. Local anesthesia with xylocain/adrenalin was applied to the left bucca and three punch biopsies (5 mm in diameter, 3–4 mm deep) were taken from the site. For donor group B, tissue samples were taken before wound closure on patients who underwent orthognatic surgery of the mandible. The patients underwent these corrective surgeries due to abnormal position of the mandible in relation to the base of skull, but no buccal disease or inflammation is associated with these conditions. The patients were treated under general anesthesia and local anesthesia was additionally applied. Tissue samples 20 × 10 mm in size were taken bilaterally from the mucosa. Matched blood samples from donor group B were collected at the time of the procedure. After collection, the biopsies were stored at 4°C in serum‐free RPMI (ThermoFisher Scientific, Waltham, MA, USA) supplemented with 50 μg/mL gentamicin (ThermoFisher Scientific) and 100 μg/mL normocin (InvivoGen, San Diego, CA, USA). Biopsies intended for qPCR analysis were stored in RNAlater (QIAgen, Venlo, Netherlands) at −20°C. Biopsies intended for in situ microscopic analysis were submerged in OCT Cryomount (HistoLab, Askim, Sweden), snap‐frozen in liquid nitrogen, and then stored at −80°C. Sample processing for flow cytometry All collected samples were processed within 3 h of collection. Buccal biopsies were placed into serum‐free RPMI supplemented with 50 μg/mL gentamicin and 100 μg/mL normocin and then incubated with 1 mg/mL DNase I and collagenase A (both from Roche, Penzberg, Germany) at 37°C with shaking at 800 rpm for 1 h. After incubation, the reaction was stopped by addition of fetal calf serum (FCS; Sigma‐Aldrich, St Louis, MO, USA) to a final concentration of 10%. The biopsies were then pressed through a 100 μm cell strainer in order to detach loose cells. The cells were then washed in PBS and incubated in RBC lysis buffer for 10 min at RT to remove any erythrocyte contamination. The cells were washed again in PBS and stained for flow cytometry. Donor‐matched PBMCs were isolated from blood samples by Ficoll‐Hypaque density gradient centrifugation using Lymphoprep (Axis‐Shield, Dundee, Scotland). The PBMC layer was washed twice with PBS, and incubated in RBC lysis buffer for 10 minutes at room temperature to remove erythrocyte contamination. The cells were washed again in PBS and 106 cells were stained for flow cytometry. In situ staining In situ staining was performed on 8‐μm‐thick sections of frozen biopsies, as previously described 22. Sections were fixed in 2% formaldehyde and stained sequentially. Antibody reagents used for tissue staining are listed in Supporting Information Table 3. The tissue sections stained for Vα7.2 in combination with IL‐18Rα were scanned into digital images using a Pannoramic 250 Flash Slide Scanner (3DHistech, Budapest, Hungary). The distance measurement was performed using the digital microscope application CaseViewer (3DHistech), where the distance from the surface of the double‐positive cells to the basal membrane was measured. The tissue sections stained for HLA‐DR in combination with MR1, and Vα7.2 in combination with CD3 were visualized using DMR‐X microscope (Leica, Weitzlar, Germany) and images were acquired with a Retiga 2000 R camera (Qimaging, Surrey, Canada). Functional assay One million lymphocytes in suspension were cultured overnight in RPMI +10% FCS, supplemented with 100 μg/mL normocin and 50 μg/mL gentamicin. After overnight incubation, they were activated using Leukocyte Activation Cocktail (PMA/ionomycin) (BD Biosciences, San Jose, CA, USA) in the presence of GolgiPlug (monensin) for 6 h. At the end of the incubation, the cells were stained and analyzed by flow cytometry. Flow cytometry and antibodies Cells in suspension were stained for surface antigens in FACS buffer (PBS with 2 mM EDTA and 2% FCS) for 20 min at 4°C. Afterwards, they were washed in FACS buffer and permeabilized using the transcription factor fixation and permeabilization buffer (BD Biosciences) for 30 min at 4°C. Following permeabilization, cells were washed twice in transcription factor wash and permeabilization buffer (BD Biosciences), and then stained for intracellular antigens in the same buffer for 20 min at 4°C. PE‐conjugated human MR1:5‐OP‐RU tetramer was obtained from the NIH Tetramer Core Facility. For tetramer staining, cells in suspension were incubated with MR1:5‐OP‐RU tetramer for 40 min at room temperature and then washed with FACS buffer prior to surface antibody staining. Monoclonal antibody reagents used in the study are listed in Supporting Information Table 4. After staining, cells were washed and analyzed using an LSRFortessa flow cytometer (BD Biosciences) equipped with 355, 405, 488, 561, and 639 nm lasers. In addition to the antibodies, cells were stained with LIVE/DEAD Fixable Dead Cell Stain (Near‐Infrared or Aqua; ThermoFisher Scientific). Quantitative RT‐PCR qRT‐PCR was performed to determine the mRNA expression of TCRs Vα7.2‐Jα33, Vα7.2‐Jα20, and Vα7.2‐Jα12 as well as the constant Cα chain, in healthy oral mucosa and blood. Briefly, total RNA was extracted from buccal mucosa and PBMCs using TRIzol reagent (ThermoFisher Scientific). For reverse transcription, 250 ng of RNA was used in a 15 μL total reaction volume using the IScript cDNA Synthesis kit (BioRad, Hercules, CA, USA). For amplification, a 20 μL supermix reaction was prepared accordingly: 1 μL cDNA, 5 μL SsoAdvanced™ Universal® SYBR Green (BioRad), 1 μL of each primer at a final concentration of 500 nM, and nuclease free H2O. Primer sequences as well as annealing temperatures for each of the primer sets are listed in Supporting Information Table 5. qPCR was performed using 7500 Fast real time PCR system (Applied Biosystems, Waltham, CA, USA) with the following cycling conditions: 1 cycle at 95°C for 5 min, then 40 cycles at 94°C for 10 s, 58°C or 60°C depending on primer for 30 s, and 72°C for 27 s. The relative abundance of each Vα7.2‐Jα was determined as relative to Cα by the comparative ΔΔCT method. Software and statistical analysis Analysis of flow cytometric data was performed using FlowJo 10 (FlowJo LLC, Ashland, OR, USA), and microscopic images were processed using Image‐Pro Premier 9.3 (Media Cybernetics, Rockville, MD, USA). Statistical tests were performed using GraphPad Prism version 7.0c for Mac OS X (GraphPad Software, La Jolla, CA, USA). Statistical significance was assessed using Wilcoxon matched pairs test for paired data, and Mann–Whitney U‐test for unpaired data. For data presented in Fig. 5, analysis and presentation of distributions were performed using SPICE version 5.1, downloaded from http://exon.niaid.nih.gov 48. Comparison of distributions was performed using a Wilcoxon matched pairs test as described 48. For all statistical analysis, p‐values below 0.05 were regarded as significant. Acknowledgements The authors wish to acknowledge the contribution of Sam Chehrehgosha, Angelica Kroonder, Emelie Molin, and Beatrice Wiberg in recruiting study volunteers and gathering oral biopsies. This research was supported by grants to JKS from the Swedish Research Council (2016‐03052), the Swedish Cancer Society (CAN 2017/777), and the US National Institutes of Health (R01DK108350). Grants to M.S.C. were from the Foundation for Odontological Research (OF11211233), and the Swedish Cancer Society (CAN 2016/731). Further support to E.L. was from the Swedish Research Council (2015‐00174) and Marie Skłodowska Curie Actions, Cofund, Project INCA 600398. J.D. was supported by Fundação para a Ciência e a Tecnologia (SFRH/BD/85290/2012, doctoral fellowship), through program QREN‐POPH‐typology 4.1. The MR1 tetramer technology was developed jointly by Dr. James McCluskey, Dr. Jamie Rossjohn, and Dr. David Fairlie, and the material was produced by the NIH Tetramer Core Facility as permitted to be distributed by the University of Melbourne. The authors wish to thank the healthy volunteers that contributed time and effort to sample donation for this study. Author contributions J.K.S., E.L., and M.S.C. conceived the original research idea and study design. M.J.S., H.D., M.M., A.T., J.D., E.L., M.S.C., and J.K.S. designed experiments. M.J.S., H.D, A.G., and J.E. conducted experiments. M.J.S., H.D., and A.G. analyzed experimental data. R.H., S.A., and C.K.W. recruited study volunteers and collected essential human samples. M.J.S. and J.K.S. wrote the manuscript. All authors reviewed and commented on the manuscript. Conflict of interest The authors declare no commercial or financial conflict of interest. Supporting Information References Abbreviations IEL intraepithelial lymphocyte MAIT mucosal‐associated invariant T MR1 MHC‐Ib‐related protein 1 PLZF promyelocytic leukemia zinc finger protein
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3 RESULTS A total of 10 638 citations were identified from the electronic and manual search. After removing duplicates (n = 767) and non‐applicable references (n = 9620), 251 citations were screened, of which 92 met the inclusion criteria (Figure 1).14-105 Baseline characteristics of the included manuscripts, study quality and studies reporting negative results are provided in Table S1, S2 and S3 respectively. Data from several included studies are only presented in tables.14-29 Figures 2 and 3 provide an overview of different predictive molecular markers grouped by underlying biological mechanism. 3.1 Anti‐TNF therapy (IFX // ADA // GLM // CZP) 3.1.1 (Pharmaco) genomics An overview of predictive genetic biomarkers for anti‐TNF response is presented in Figure 2 and Tables 1 and 4. Reference (year) Response definition Biomarker Association Predictive value Bank (2014) Clin Resp: based on three‐step scale CD SNP rs5030728 (TLR4 G>A) Clin NR OR (adj): 0.38 [0.15‐0.96] P = 0.04 SNP rs352139 (TLR9 1174G>A) Clin NR OR (adj): 0.38 [0.16‐0.94] P = 0.04 SNP rs4149570 (TNFRSF1A‐609G>T) Clin Resp OR (adj): 5.16 [1.14‐23.39] P = 0.03 UC SNP rs11938228 (TLR2 C > A) Clin NR OR (adj): 0.26 [0.08‐0.92] P = 0.04 SNP rs4696480 (TLR2 A > T) Clin NR OR (adj): 0.29 [0.12‐0.70] P = 0.01 SNP rs3804099 (TLR2 597 T>C) Clin Resp OR (unadj): 2.47 [0.98‐6.23] P = 0.05 SNP rs5030728 (TLR4 G > A) Clin Resp OR (unadj): 2.59 [1.08‐6.18] P = 0.03 Bank (2018) Clin Resp: three‐step scale to reflect max response 22 W after initiation CD heterozygous genotype of TLRS 936 T>C (rs5744174) NR OR: 0.24 [0.11‐0.53], P = 0.008 homozygous variant genotype of IFNGR2 T>C (rs8126756) NR OR: 0.36, 95% CI: 0.16‐0.81, P = 0.01 UC heterozygous genotype of IL128B ‐ 10993 G>C (rs3212217) NR OR: 0.09, 95% CI; 0.01‐0.65, P = 0.02 heterozygous genotype of IFNGRI ‐ 56 T> C (rs2234711) NR OR: 0.29, 95°/o CI: 0.11‐0.78, P = 0.01 homozygous genotype of TBX21 ‐ 1514 T>C (rs17250932) NR OR: 0.06, 95% CI: 0.01‐0.80, P = 0.03 homozygous genotype of JAK2 T>C (rs12343867) NR OR: 0.17, 95% CI: 0.03‐0.85, P = 0.03 hetero+homoz. genotypes of IL128 −10993 G > C (rs3212217) NR OR: 033, 95% CI: 0.15‐0.69, P = 0.004 hetero+homoz. genotypes of IL 18‐607 C > A (rs1946518) Clin Resp OR: 2.14, 95% CI: 1.06‐4.32, P = 0.03 CD +UC: heterozygous genotype of IFNGRI ‐ 56 T>C (rs2234711) NR OR: 0.57, 95% CI: 034‐0.96, P = 0.04 homozygous genotype of IL 126 −10993 G > C (rs3212217) Clin Resp OR: 10.40, 95% CI: 131‐82.41, P = 0.03 hetero+homoz. genotypes NLRP3 29940 C > G (rs10754558) Clin Resp OR: 1.60, 95% CI: 1.02‐2.52, P = 0.04 Barber (2016) Clin PNR: Clin NR by W12 or Th cessation within 4 months of induction. DR: Clin response ≥24 M prediction model: 15 SNPs (GRS 5‐20) Clin PNR AUC 0.929; OR 2.65 [1.94‐3.61], P = 6 x 10‐10 prediction model: 16 SNPs (GRS 6‐23) Clin DR AUC 0.83; OR 1.6 [1.41‐1.83], P = 2 x 10‐12 prediction model: clinical and genome Clin DR AUC 0.85 prediction model: clinical and genome Th cessation HR 0.89 [0.85‐0.93], P = 4 x 10‐8 Billiet (2016) Biochem; Not Specified FCGRT promotor VNTR2/VNTR3 genotype Drug expos Not specified Dezelak (2016) Clin Resp: IBDQ >170 or increase in >22 pts compared to baseline. Biochem Resp: CRP <3 mg/L or decrease >25% from baseline SNP rs9373839 (ATG5) Allele C and haplotypes C/C & C/T Clin Resp 4.2‐fold higher chance for CResp; P = 1.13x10‐0 SNPs rs9373839 and rs510432 (ATG5) haplotype C/G Clin Resp 4.9% higher IBDQ score; P = 1.31x10‐06 SNPs rs9373839 and rs510432 (ATG5) Allele C and haplotypes C/G Clin Resp 36% higher chance for CResp; P = 8.34x10‐7 SNP rs1130864 (CRP) ≥1 allele C Clin&Biochem Resp 10‐fold higher chance for CResp and fourfold higher chance for BResp Gonsky (2014) Clin; Not Specified SNP rs1861494 (IFNG +2109) T allele carriage (T/T and T/C) vs C allele (C/C) ASCA+ P < 0.015, No quant pred data Haritunians (2009) MR‐UC: UC requiring colectomy (refractory to drugs). Non‐MR‐UC: colectomy for cancer or no colectomy. Prediction model: 46 SNPs MR‐UC 48% of the variance for colectomy explained. HR 1.313; AUC 0.91; Sens 0.793; Spec 0.858 Score of 44 & 47 generated test Sens and Spec of over 90% Hlavaty (2005) Clin Resp (partial): LCD: decrease≥70 pts (W4). FCD: decrease ≥50% in fistula drainage (W10) Clin Rem: LCD: CDAI<150 (W4). FCD: cessation of fistula drainage (W10). SNP rs1800682 (FAS) haplotype C/C or C/T vs T/T (minor allele: T) Clin Resp OR 0.11 [0.08‐0.56]; P = 0.002 SNP rs4645983 (CASP9) allotypes T/T vs C/C or C/T (minor allele: T) Clin Resp OR 1.50 [1.34‐1.68]; P = 0.04 SNP rs763110 (FAS)Fas ligand −843 CC/CT genotype Clin Resp OR 1.66 [1.21‐2.29], P = 0.002 Hlavaty (2007) Clin Resp (partial): LCD: decrease by ≥70 points at W4. FCD: decrease ≥50% fistula drainage at W10. Clin Rem: LCD: CDAI <150 at W4. FCD: complete cessation of fistula drainage at W10. Prediction model: Apoptotic pharmacogenetic index (API) (ranging from low to high apoptotic response (0‐3)) consisting of three SNPs: Fas ligand −843 C/T (0 pt: if TT and 1 point if CT/CC) Fas −670 G/A (0 pt if TT and 1 pt if AG/AA) Caspase9 93 C/T (0 pt if TT/CT and 1 pt if CC) Clin Resp API ≤1 (n = 59): R in LCD (50%) and FCD (39.5%). API of 2 (n = 158): CR and CResp in LCD (56.1% & 73.8%) and in FCD (44.9% & 85.7%). API =3 (n = 10), CR and CResp in LCD (85.7% & 100%) and in FCD (0% & 100%) No quant pred data Koder (2015) Biochem Resp: decrease of CRP to <3 mg/L or drop in CRP >25% SNP rs10210302 (ATG16L1) genotypes C/T or T/T vs C/C Biochem Resp OR 9.44 [2.49‐35.83], P(corrected) = 0.027 Lopez‐Hernandez (2014) Clin Resp: improvement in HBI or clinical observation. Clin NR: no change in HBI or exacerbation SNP rs1800629 (TNFα −308G/A) allele A and G/A vs G/G Clin NR Cp<0.05 No quant pred data %Resp vs %NR: Clin NR Clin Resp Clin NR ‐308A allele: 6% vs 27% Cp=0.026 ‐308GG genotype: 88% vs 44% Cp=0.029 ‐308GA genotype: 12% vs 55% Cp=0.017 No quant pred data Louis (2004) Biochem Resp (complete): normal CRP at W4. Biochem Resp (partial): decrease ≥25% at W4 SNP rs396991 (FCGR3A) allotype T/T vs T/G or G/G (WT) Biochem Resp RR 1.43 [1.27‐1.61], P = 0.0002 Louis (2006) Biochem Resp: ≥25% reduction in CRP at both W2 and W6 from BL SNP rs396991 (FCGR3A) allotype V/V vs V/F and F/F Biochem Resp W6 CRP reduction: −79.4%, −76.5% and −64.3%; P = 0,085, No quant pred data Mascheretti (2002) Clin Resp: cohort 1: decrease CDAI >70 points from baseline to W4; cohort 2: decrease CDAI>70 points from baseline to W2. Clin Rem: CDAI<150 SNP rs1800629 (TNF), haplotype G/A or A/A vs G/G (minor allele: A) SNP rs1061622 (TNFRSF1B), haplotype T/G or G/G vs T/T (minor allele: G) Clin Resp Clin Resp Not specified OR 0.88 [0.57‐1.3] Matsukura (2008) Clin Resp: improvement in HBI or clinical observation. Clin NR: no improvement or exacerbation SNP rs767455 (TNFRSF1A), A/G and G/G vs A/A (WT) SNP rs1061624 & rs3397) (TNFRSF1B), rs1061624 A allele and rs3397 T allele Clin NR Clin NR OR 0.22 [0.06‐0.76] & OR 0.26 [0.08‐0.90]; P < 0.05 5% Resp vs 18% NR, χ2 = 6.4, P = 0.01, No quant pred data Medrano (2014) Clin Resp (partial): LCD: decrease HBI >3 and no CS. FCD: reduction ≥50% in the number of draining fistulas. Clin Rem: LCD: HBI<4 and no CS. FCD: complete closure of fistulas. SNP rs1061624 (TNFRSF1B), haplotype A‐rs3397_T Clin NR OR 1.78 [1.09‐2.90], P = 0.015 Moroi (2013) Biochem Resp: ΔCRP & ΔCRP% SNP rs396991 (FCGR3A‐158), allotype V/V vs V/F or F/F Biochem Resp ΔCRP, P < 0.001; ΔCRP%, P = 0.044, No quant pred data Netz (2017) Clin Resp: in accordance with the treating physician decision Fas ligand SNP (rs763110) A (minor) TNF gene −308 allele NR NR OR 4.30 [1.45‐12.8], P = 0.009 OR 2.88 [1.1‐8.22], P = 0.049 Pierik (2004) Biochem Resp: >12 mg/L reduction in CRP. Biochem Rem: CRP <3 mg/L. SNP rs767455 (TNFRSF1A), A36G carriage Biochem Resp OR 0.47 [0.234‐0.946], P = 0.0343 Repnik (2016) Clin Resp: increase in IBDQ >22 or IBDQ >170 SNP rs2071303 (HFE), A/G or G/G vs A/A genotype Clin Resp W12: OR 3.467 [1.149‐10.463] P = 0.037. W20: OR 4.832 [1.519‐15.367] P = 0.009. Allele G vs A carriage: W20: OR 3.542 [1.355‐9.258] P = 0.0082, No quant pred data Spalinger (2016) Clin NR: 1. breakthrough/LOR, 2. PNR 3. Stop due to side effects/intolerance. SNP rs1893217 (PTPN2), variant haplotypes C/T or C/C vs T/T Clin Resp (n)Resp vs (n)NR Genotype: CC: 7 vs 5 ‐ CT: 37 vs 39 ‐ TT: 71 vs 109 Existence of C‐allele: CC/CT: 44 vs 44 ‐ TT: 71 vs 109 P = 0.05, No quant pred data Steenholdt (2012) Clin Resp: PGA +biochemical markers SNP rs1061622 (TNFRSF1B) minor allele carriage SNP rs976881 (TNFRSF1B), minor allele carriage Clin Resp DR LOR OR 4.2 [1.2‐18.2], P = 0.014 OR 5.5 [1.5‐25.5], P = 0.007 OR 3,3 [1.2‐9.1], P = 0.014) (Homozygosity: OR 19, P = 0.006) IBD: inflammatory bowel disease; CD: Crohn's disease; UC: ulcerative colitis; LCD: luminal Crohn's disease; FCD: fistulising Crohn's disease; MR‐UC: medical refractory ulcerative colitis; M: months; W: weeks; D: days; FU: follow‐up; CDAI: Crohn's Disease Activity Index; CAI: colitis activity index; HBI: Harvey Bradshaw Index; PCDAI: Paediatric Crohn's Disease Activity Index; PUCAI: Paediatric Ulcerative Colitis Activity Index; PGA: Physician's Global Assessment score; ULN: upper limit of normal; Hb: haemoglobin; CRP: C‐reactive protein; ESR: erythrocyte sedimentation rate; FC: faecal calprotectin; CK: cytokine; PBMC: peripheral blood mononuclear cell; TNF: tumour necrosis factor; IFX: infliximab; ADA: adalimumab: UST: ustekinumab; PCB: placebo; CS: corticosteroids A‐D‐A: anti‐drug antibodies; Clin: clinical; Biochem: biochemical; Rem: remission; Resp: Response; NR: nonresponse; PNR: primary nonresponse; DR: durable response; Sust: stained; LOR: loss of response; Th cessation: Therapy cessation; Drug expos: Drug exposure; SSFR: sustained steroid free remission; RB: rectal bleeding; pts: points; OR: odds ratio; HR: hazard ratio; Sens: sensitivity; Spec: specificity; PPV: positive predictive value; NPV: negative predictive value; SNP: single nucleotide polymorphism; WT: wild type; GRS: genetic risk score; LH: likelihood; FCGRT: Fc Fragment Of IgG Receptor And Transporter; MPV: mean platelet volume; IL: interleukin; Cp: Corrected p‐value; (n): number; No quant. pred. data: No quantitative predictive data. Fc‐receptors Several studies reported on the association between FCGR3A genotype and response to anti‐TNF treatment.28-31 The V/V allotype was associated with a significantly higher proportion of CD patients (100%) achieving a CRP decrease in response to infliximab compared to the V/F or F/F allotypes (70%).30 This finding was confirmed by Moroi et al and in a sub‐analysis of the ACCENT I trial.29, 31 Due to close location of the FCGR3A and the CRP genes, a potential false‐positive association was investigated and excluded.32 Genetic variations within the neonatal Fc‐receptor (FcRn gene) were associated with pharmacokinetic changes for IFX and ADA. Heterozygosity for the VNTR2/VNTR3 genotype led to a 14% (P = 0.03) and 25% (P = 0.007) reduction in induction drug concentrations compared to homozygosity VNTR3 for IFX and ADA respectively.33 ATG16L1 The autophagy related gene ATG16L1 was linked to anti‐TNF response in two studies.28, 34 Patients with the ATG16L1 T/T and C/T genotypes had a significantly greater CRP response to adalimumab than patients with the C/C genotype (85% vs 37.5%; OR 9.44 [2.49‐35.83], P = 0.027).28 More recently however, the association between autophagy and anti‐TNF response was not confirmed in a large retrospective study.35 Apoptosis A number of studies reported an association between genes related to apoptosis and anti‐TNF response.28, 34, 36, 37 Fas ligand TT genotype and caspase‐9 CC/CT genotypes were associated with low response to IFX in luminal CD. In fistulising CD, Fas ligand‐843 CC/CT genotype was the only predictor of response.36 Conversely, the CC genotype vs a TC or TT genotype was associated with primary nonresponse in CD (OR 4.3 [1.45‐12.8], P = 0.009).38 TNF/TNF‐receptor genes Several studies looked at TNF‐signalling pathways and anti‐TNF response.39-47 A genetic alteration in the TNF region (the lymphotoxin α locus, also known as TNF‐β) was associated with clinical nonresponse to a single infusion of infliximab in CD (P = 0.007).39 Other studies found no significant association between variation in the TNF region (eg, the TNF promoter region) and treatment response.40, 41 Recently however, the presence of the minor allele (A) for the TNF gene (rs1800629) was associated with primary nonresponse (OR 2.88 [1.1‐8.22], P = 0.049).38 Several studies reported on single nucleotide polymorphisms (SNPs) within the TNF‐receptor superfamilies (TNFRSF) 1A and 1B. Regarding TNFRSF1A, higher response rates were observed in CD patients homozygous for the TNFRSF1A‐609G>T genotype (OR 5.16 [1.14‐23.39], P = 0.03).42 Minor allele carriage (G) of SNP rs767455 was associated with low clinical anti‐TNF response (OR 0.47 [0.23‐0.95], P = 0.034), a finding that was replicated by a different study group (OR 0.26 [0.08‐0.90]).43, 44 With respect to TNFRSF1B, an increased frequency in the haplotype conformed by two SNPs (rs1061624_A‐rs3397_T) was found in anti‐TNF nonresponders in both a Japanese and Caucasian CD population (P = 0.01 and OR 1.78 [1.09‐2.90], P = 0.015, respectively).43, 45 Conversely, minor allele (G) carriage of the TNFRSF1B SNP (rs1061622) was associated with improved initial (OR 4.2 [1.2‐18.2], P = 0.014) and sustained clinical response to anti‐TNF (OR 5.5 [1.5‐25.5], P = 0.007).46 However, the latter association (OR 8.5 [0.9‐206.3]) could not be confirmed.47 Recently, a similar association between this specific SNP (TNFRSF1B, rs1061622) and clinical response was reported (OR 1.52 [0.79‐3.04], P = 0.023).45 In addition, minor allele carriage of TNFRSF1B (rs976881) was also discovered to be associated with loss of response to IFX (OR 3.3 [1.2‐9.1], P = 0.014).46 Finally, Pierik et al did not find an association between TNFRSF1B (rs1061622) and anti‐TNF response.44 NOD2/CARD15, CRP, IL23R and IL12 No significant association with treatment response was found either for the IBD susceptibility variants of NOD2/CARD15 or for variations of the CRP genotype.32, 48-51 UC patients carrying the homozygous IBD risk‐increasing IL23R SNPs were more likely to respond to infliximab than patients with the risk‐decreasing variants (74.1% vs 36.6%, P = 0.001).52 A recent study observed that the heterozygous genotype of IL12B—10993 G > C (rs3212217) was associated with nonresponse within 22 weeks after initiation in UC (OR 0.24 [0.11‐0.53], P = 0.008).53 Genetic risk models Several predictive genetic models for treatment response to anti‐TNF therapy have been suggested.34, 37, 54, 55 Hlavaty et al developed an algorithm—comprising three apoptotic SNPs (Fas ligand −843 C/T, Fas −670 G/A and caspase‐9 93 C/T)—to predict clinical response to the initial IFX infusion in CD.37 Another risk model with 46 SNPs, was found to be predictive of colectomy as a measure of refractory UC (Area under the curve value (AUC) 0.91, sensitivity 0.79 and specificity 0.85).55 Furthermore, three genetic IBD susceptibility SNPs, rs2836878 (21q22/BRWD1) combined with the microbial biomarker pANCA predicted primary nonresponse to anti‐TNF in paediatric UC patients (AUC 0.98, sensitivity 0.95, specificity 0.88 and positive likelihood ratio 8).54 Recently, two additional models were developed for primary nonresponse and sustained response to anti‐TNF treatment in CD. The genetic risk score—comprising 15 SNPs—was the only independent predictor of primary nonresponse (OR 2.65 [1.94‐3.61], P < 0.0001). In the risk model for sustained response—comprising 16 SNPs—each one‐point increase was associated with a 60% higher likelihood of sustained response (AUC 0.929; OR 1.6 [1.41‐1.83], P = 2x10–12).34 Recently, the combination of two‐risk genotypes, involving both apoptosis and the TNF region, was associated with primary anti‐TNF nonresponse (OR 4.76 [1.35‐16.77], P = 0.015).38 3.1.2 Gene expression An overview of predictive gene expression biomarkers is presented in Tables 2 and 4. Reference (year) Response definition Biomarker Association Predictive value Peripheral blood Li (2016) Endo Resp: Mayo/SES‐CD/Rutgeerts score; Not Specified lamina propria CD4+ T‐cell subsets. Endo Resp Reduced prevalence of Gata3‐expressing cells in the CD cohort (P = 0.002), No quant pred data Intestinal tissue Arijs (2009) Endo Resp: MH = Mayo ≤1. H Resp: Geboes ≤1 osteoprotegerin, (TNFRSF11B), stanniocalcin‐1 (STC1), prostaglandin‐endoperoxide synthase 2 (PTGS2), IL‐13 receptor α 2 (IL13Rα2) and IL‐11 Endo&Hist Resp Accuracy of 89.1% (41/46). Sens: 95% (19/20); Spec: 85% (22/26) Arijs (2010) Endo Resp: MH, Hist Resp: ≥ 3 pts decrease on the geboes score TNF induced protein 6 (TNFAIP6), S100A8, IL11, G0/G1switch 2 (G0S2) and S100A9 Endo&Hist Resp CDc: top 5 genes: (accuracy 100%). CDi: no association, No quant pred data Atreya (2014) Clin Resp: CDAI decrease ≥100 pts (12 W). Endo Resp: MH = absence of ulcers Number of membrane‐bound TNF (mTNF) expressing cells Clin&Endo Resp High mTNF‐group (≥20 cells/confocal image) vs low‐group (<20): higher probability of R (92% vs 15%). Accuracy 88%; Sens 92%; Spec 85%; PPV 85%; NPV 92% Halloran (2014) Endo Resp: total mayo of 0 or 1 Principal component 1 (PC1) (disturbance in gene expression seen in TCMR (kidney/heart) Endo Resp Higher pre‐treatment PC1 (UC: P < 0.03; CD: P < 0.001), No quant pred data Viazis (2017) Endo Resp: MH=endoscopic mayo 0 lower Th1‐defining T‐bet and higher Th17‐defining Rorc‐p Endo Resp P < 0.05, No quant pred data West (2017) Endo&H Resp: complete disease resolution BL Oncostatin M‐associated inflammatory module expression: Module‐low vs Module‐high Endo&Hist Resp Relative risk = 5, 95% CI = 1.4‐17.9, P = 0.0006 Yamada (2017) CD: Clin Resp: decrease ≥100 from BL, or <150 when BL was≤248 UC: Clin Resp: decrease ≥3 full Mayo or ≥2 points in clinical Mayo with decrease ≥1 in RB Higher expression of Bmi1 PNR Relative Bmi1 expression Resp vs NR: 1.28 ± 0.14 vs 2.10 ± 0.23, P = 0.0039, No quant pred data IBD: inflammatory bowel disease; CD: Crohn's disease; CDc: crohn's colitis; CDi; crohn's ileitis: UC: ulcerative colitis; M: months; W: weeks; FU: follow‐up; BL: baseline; CDAI: Crohn's Disease Activity Index; HBI: Harvey Bradshaw Index; SES‐CD: simple endoscopic score for Crohn's disease; TNF: tumour necrosis factor; IFX: infliximab; ADA: adalimumab: Clin: clinical; Endo: endoscopic; Hist: histological; Resp: response; NR: nonresponse; PNR: primary nonresponse; MH: mucosal healing; pts: points; TCMR: T‐cell‐mediated rejection of organ transplants; Sens: sensitivity; Spec: specificity; PPV: positive predictive value; NPV: negative predictive value; No quant pred data: No quantitative predictive data. Peripheral blood A reduced number of Gata3+‐expressing T helper cells was associated with endoscopic response to anti‐TNF in CD but not UC, which could be associated with a reduced number of eosinophils.56 Recently, a decrease in peripheral blood mononuclear cell (PBMC) expression of CD14 and CD86 at both week 2 and week 14 compared to baseline was shown to be associated with short term clinical and endoscopic response to infliximab.57 Intestinal tissue A mucosal gene signature for response to infliximab in both colonic CD and UC was identified.58, 59 In colonic CD, the top five differentially expressed genes (TNFAIP6, S100A8, S100A9, IL‐11 and G0S2) predicted endoscopic and histological response with 100% accuracy.59 In UC, a combination of five innate immunity gene expression profiles (TNFRSF11B, STC1, PTGS2, IL13Ralpha2 and IL11) predicted response with 89% accuracy (sensitivity 95% and specificity 85%).58 An association between mRNA patterns—reflecting general inflammation, dedifferentiation and tissue damage—and nonresponse to anti‐TNF has been reported. This pattern was similar to that seen in organ transplant rejection.60 Ongoing increased regulatory T‐cell CD39 expression was associated with anti‐TNF response and resulted in decreased suppression of inflammation in a consecutive IBD mouse model.61 Another approach to predict response is by direct visualisation of a target molecule. A high number of membrane bound TNF‐expressing mucosal cells, as identified by in vivo molecular imaging techniques, was associated with increased probability of anti‐TNF response (92% vs 15%; accuracy 88%, positive predictive value (PPV) 85%, negative predictive value (NPV) 92%).62 Furthermore, clinical response to anti‐TNF in UC was associated with low baseline mucosal mRNA expression of IL‐6, IL‐1β, IL‐17A and IFN‐γ.63 Finally, mucosal oncostatin M and its receptor expression were recently shown to be associated with disease activity and pre‐treatment expression was associated with subsequent endoscopic anti‐TNF nonresponse in both CD and UC.64 3.1.3 Proteins An overview of predictive protein markers is presented in Tables 3 and 4. Reference (year) Response definition Biomarker Association Predictive value Anti‐TNF Algaba (2014) Clin Resp: ≥5 pt reduction in modified Truelove‐Witts index or ≥70 pt reduction in CDAI VEGF; Ang1 Clin Resp NR Low VEGF levels at BL (R vs NR: 453.5 ± 250.7 vs 667.5 ± 153.9 pg/mL) and before 2nd and 3rd dose (P < 0.05). High Ang1 at BL (AUC 0.7) High VEGF at BL (AUC = 0.8. Cutoff: 658.36 pg/mL; Sens 85.7%; Spec 78.6% Baird (2016) Clin Resp: CDAI<150; CAI ≤4, Biochem Resp: CRP≤10 mg/L TNF, IL‐1β, IL‐10, IFN‐γ, IL‐6, plasmacytoid DC, IRAK4 NR Clin&Biochem Resp UC: Increased TNF, IL‐1β, IL‐10 and IFN‐γ at BL. Lower TNF & IL‐1β production by TLRs and reduced TLR0‐induced IL‐6 and TLR‐3/4/8/9‐induced IL‐10. Lower pDC frequency's (P < 0.01). Increased IRAK4 upon TLR‐9 stimulation compared to BL (P = 0.03). No IRAK4 reduction upon TLR‐2/4/7 stimulation. No quant pred data Lower total IRAK4 levels upon TLR stimulation, No quant pred data Biancheri (2015) Clin Rem: Not Specified, Endo Resp: complete MH Serum levels of cleaved IgG and antihinge autoantibodies PNR NR have higher serum levels of MMP3‐/MMP12‐cleaved endogenous IgG than both healthy controls and Resp and higher levels of antihinge autoantibodies than Resp (both significant), No quant pred data Billiet (2017) Clin Resp: PGA clear clinical benefit after three infusions. PNR: absence of clinical improvement TNF/CRP ratio at BL higher IL8 at BL IFN‐ɣ & IL‐6 decrease between BL and W2 and W6 resp PNR PNR Clin Resp OR 2.8 [1.4‐5.5], P = 0.003 BL levels IL8 Resp vs PNR (median(IQR)): 11.3 pg/mL (7.3‐18.7) vs 20.3 pg/mL (8.9‐61.1), P = 0.01, No quant pred data P < 0.05, No quant pred data Caneparo (2016) UC: Clin Rem: partial Mayo ≤2 with no subscore >1, Clin Resp: decrease partial Mayo ≥3 and ≥30% from BL with decrease RB ≥1 or absolute RB of 1 or 0. CD: Clin Rem: HBI<4, Clin Resp: decrease HBI≥3 compared to previous IgG anti‐IFI16 antibodies at BL Clin Resp OR =0.143; 95% CI 0.027‐0.761. Feng (2017) Clin Rem: CDAI<150. Clin Resp: CDAI decrease >100. Endo Rem: MH =absence ulcers IL‐9 levels at W14 to predict Resp at W30 Clin Rem Endo Rem NR AUC: 0.803, cut‐off 17,4 (Sens 0,80; spec 0.75; PPV 44.4; NPV 93.7) AUC: 0.752, cut‐off 15.5 (Sens 0.63; spec 0.87; PPV 85.0; NPV 66.7) higher IL‐9 levels at W14 P = 0.003, No quant pred data Ferrante (2007) Clin Resp: absence of diarrhoea and RB. Partial Clin Resp: improvement but with RB. pANCA+/ASCA‐ (n = 87) Clin Resp (suboptimal) OR 0.4 [0.16‐1.00] P = 0.049 Kevans (2015) Clin Resp at 1 year: no symptoms, CS, salicylate therapy and no colectomy. Anti‐OmpC positivity NR OR 0.14 [0.03‐0.6], P = 0,04; in multivariable model: OR 0.14 [0.03‐0.6] P = 0.006 Magnusson (2013) Clin Resp: decrease in Mayo ≥3 compared with BL, prior to fourth treatment dose. CD4+ and CD8+CD25+ T cells (W2) Annexin V + CD4+ and CD8+ T cells (W2) Serum sCD25 (W2) Serum TNFRII (W2) Clin Resp Clin Resp Clin Resp Clin Resp Cut‐off CD4+CD25+: decrease ≥0.65%; Sens 84.6%. Spec 87.5%. Cut‐off CD8+CD25+ T cell: decrease ≥0.14%; Sens 69.2%; Spec 93.8% Cut‐off: decrease ≥98 pg/mL with Sens 66.7%; Spec 77.8% Cut‐off: decrease ≥98 pg/mL with Sens 66.7%; Spec 77.8% Cut‐off: decrease ≥255 pg/ml; Sens 75%; Spec 72.2% Magnusson (2015) Clin Resp: reduction in Mayo score ≥3 compared with BL (evaluation before 4th infusion). Prediction model: T‐cell surface activation receptor CD25 & IL‐5 Clin Resp R2=0.63; prediction accuracy: 85% Nishida (2017) Clin Resp: partial mayo reduction ≥3 with a decrease ≥30% from BL and decrease RB ≥1 or absolute RB 0 or 1. LOR: clinical relapse BL higher Neutrophil‐to‐lymphocyte ratio (NLR) LOR ROC: cut‐off 4.488 Sens 78.6% Spec 78.3% HR: 3.86 P = 0.023 Reich (2016) Clin Rem: modified HBI<5. Clin Resp: reduction HBI ≥3. NR: surgery or escalation before W14 Clin Rem W14: OR 3.5 [1.3‐9.7], W22: OR 4.7 [1.3‐17.2] Santos Antunes (2016) Clin NR based on PGA and/or need for surgery ANA (positive if ≥1/100) Vit D deficiency: 25(OH)D < 20 ng/mL) Clin NR Clin NR OR 20.107 [2101‐192 388] Association between VD deficiency and positive pre‐treatment ANA OR 6.015 [1,054‐51,599]) Sobolewska (2016) DR: Clin Resp for 52 W. (Clin Resp: CDAI decrease≥25% & ≥70 pts.) LOR: 1) CDAI≥175 & increase CDAI≥35% & ≥70 at ≥2 visits (≥3 W), 2) CD surgery,3) switch to episodic treatment. MPV and ΔMPV DR LOR MPV >10.3 fl at W14: Sens 67% and Spec 80%; P = 0.0019. ΔMPV between BL and W14 >0.4 fl: Sens 87%; Spec: 93% Lower ΔMPV between BL & W14 (P = 0.0003), No quant pred data Steenholdt (2016) Clin Resp: CDAI reduction ≥70 pts from BL IL‐6 and sTNF‐R2 NR (PD) Lower levels after 12 W of treatment in primary PK than PD failures (<3.1 vs 4.0, P = 0.02; 3209 vs 4740, P = 0.04), No quant pred data Zator (2014) DR: time to discontinuation of the index anti‐TNF (drug with VD level within 3 M prior to start) Vit D (<30 ng/mL) NR HR 2.13 [1.03‐4.39] P = 0.04 (with supplementation at index measure) HR 3.4 [1.14‐10.19] (no supplementation) Anti‐IL23p19 Sands (2017) Clin Rem: CDAI<150 at W8, Clin Resp: CDAI decrease ≥100 BL IL‐22 Clin Resp ≥15.6 pg/mL, P = 0.04, No quant pred data IBD: inflammatory bowel disease; CD: Crohn's disease; UC: ulcerative colitis; MR‐UC: medical refractory ulcerative colitis; M: months; W: weeks; D: days; FU: follow‐up; CDAI: Crohn's Disease Activity Index; CAI: colitis activity index; HBI: Harvey Bradshaw Index; PCDAI: Paediatric Crohn's Disease Activity Index; PUCAI: Paediatric Ulcerative Colitis Activity Index; PGA: Physician's Global Assessment score; ULN: upper limit of normal; Hb: haemoglobin; CRP: C‐reactive protein; ESR: erythrocyte sedimentation rate; GM‐CSF: granulocyte‐macrophage colony stimulating factor: IFN‐γ: interferon‐gamma; FC: faecal calprotectin; CK: cytokine; PBMC: peripheral blood mononuclear cell; TNF: tumour necrosis factor; IFX: infliximab; ADA: adalimumab: CS: corticosteroids A‐D‐A: anti‐drug antibodies; Clin: clinical; Bio: biochemical: Endo: endoscopic; Rem: remission; Resp: response; NR: nonresponse; PNR: primary nonresponse; DR: durable response; LOR: loss of response; SSFR: sustained steroid free remission; RB: rectal bleeding; BL: Baseline; PK: pharmacokinetic; PD: pharmacodynamics; pts: points; OR: odds ratio; HR: hazard ratio; Sens: sensitivity; Spec: specificity; PPV: positive predictive value; NPV: negative predictive value; SNP: single nucleotide polymorphism; GRS, genetic risk score; LH: likelihood; FCGRT: Fc Fragment Of IgG Receptor And Transporter; MPV: mean platelet volume; IL: interleukin; No quant pred data: No quantitative predictive data. Reference (year) Response definition Biomarker Association Predictive value Peripheral blood Dubinsky (2010) CD: Clin PNR: increase HBI (W10 or 4 W after last dose) or no decrease ≥3 pts. UC: Clin PNR: no decrease ≥2 pts in partial Mayo score and no improvement in the PGA subscore (W10 or 4 W after last dose) Prediction model: UC, pANCA, 3 SNPs and rs2836878 (21q22/BRWD1) Clin PNR Model: R2 = 0.82 ≥ 3/6 risk factors: AUC 0.98; Sens 0.95; Spec 0.88; accuracy 0.92 and PLR 8 Jurgens (2010) Clin Resp: CAI decrease ≥5 pts or CAI<10pts. Clin Rem: CAI ≤4 Seronegativity of pANCA IL23R variants (homozygous carriers) Clin Resp Clin Resp %seropos vs %seroneg: Resp: 15.6% vs 84.4% NR: 37.1% vs 62.9%, P = 0.037, No quant pred data Clin Resp vs NR:74.1% vs 36.6%; P = 0.001, No quant pred data Lacruz (2013) Clin Resp: CDAI >70 decrease, Clin Rem: CDAI<150. Biochem Resp: CRP >25% decrease Serum IL1‐β SNP rs1143634 (IL1‐β) (C allele) Clin Resp NR <0.64 pg/ml: 6/7 Resp vs 3/10 NR; P = 0.036, No quant pred data 50% Resp vs 84% NR, P = 0.027, No quant pred data Taylor (2001) Clin Resp: decrease in CDAI score ≥70 pnts at W4. pANCA & sANCA seropositivity LTA TNFc‐aa13L‐aa26 haplotype 1‐1‐1‐1 NR NR P = 0.003 (W4), No quant pred data P = 0.007, No quant pred data Peripheral blood & Intestinal tissue Dahlen (2015) Clin Resp: Mayo decrease ≥3 pts (W14) High mucosal mRNA expression of IL6, IL‐1β, IL‐17A and IFN‐γ Low mucosal mRNA expression of IL‐6, IL‐1β, IL‐17A, TNF and IFN‐γ NR Clin Resp Not Specified Not Specified Magnusson (2015) Clin Resp: Mayo decrease ≥3 compared with BL. Endo Resp: reduction ≥1 in Mayo (endoscopy) score (W14) Reduced CD14&CD86 expression (tissue) Reduced CCL2 (W14) (tissue) Reduced PBMC expression of CD14 & 86 (blood) Reduced CCL2 (W2 & W14) (blood) Reduced tenascin C (W2 & W14) (tissue) NR Clin&Endo Resp Clin&Endo Resp Clin&Endo Resp Clin&Endo Resp Not Specified Not Specified Not Specified Not Specified Not Specified Peripheral blood & intestinal tissue & microbiota Magnusson (2016) Clin Resp: decrease total Mayo ≥3 (incl. Endo Resp: decrease ≥1 endoscopic mayo) higher DEFA5 and ECP; lower CATH (tissue) higher circulating ECP (blood) higher abundance of F. prausnitzii (microbiota) higher levels of cFOS and EGR‐1 (tissue) higher IL‐6, IL‐12a, IL‐17A, TNF, CD154 (tissue) higher IL‐6, IL‐12a, IL‐17A, TNF expression (tissue) Clin&Endo Resp Clin&Endo Resp Clin&Endo Resp Clin&Endo Resp NR NR P = 0.001, P = 0.02, P = 0.04 resp, No quant pred data Not specified P = 0.01, No quant pred data Scatter plot, Not specified Scatter plot, Not specified median [25%‐75%] Resp vs NR: IL‐6:0.77 [0.24‐1.46] vs 1.67 [1.09‐2.34] P = 0.06 IL12a: 0.53 [0.29‐0.83] vs 0.91 [0.53‐2.81] P = 0.03 IL17a: 0.92 [0.46‐1.57] vs 1.65 [1.42‐2.27] P = 0.03 TNF: 0.26 [0.18‐1.01] vs 0.65 [0.47‐0.81] P = 0.05 No quant pred data CD: Crohn's disease; UC: ulcerative colitis; pts: points; BL: baseline; W: weeks; CDAI: Crohn's Disease Activity Index; CAI: colitis activity index; RB: rectal bleeding; SF: stool frequency; HBI: Harvey Bradshaw Index; PGA: Physician's Global Assessment score; CRP: C‐reactive protein; Clin: clinical; Biochem: biochemical: Endo: endoscopic; Rem: remission; Resp: response; NR: nonresponse; PNR: primary nonresponse; CS: corticosteroids; PBMC: peripheral blood mononuclear cell; Ig: immunoglobulin; TNF: tumour necrosis factor; IFNγ: interferon gamma; mRNA: messenger RNA; pANCA: perinuclear anti‐neutrophil cytoplasmic antibody; IL: interleukin; CCL2: C‐C motf chemokine ligand 2; Sens: sensitivity; Spec: specificity; PLR: positive likelihood ratio; SNP: single nucleotide polymorphism; No quant pred data: No quantitative predictive data. Peripheral Blood Cytokines and inflammatory cells Low circulating IL‐1β concentrations were associated with clinical response to IFX in CD.41 Decreased frequencies of CD25+ T cells, increased annexin V+ CD4+CD8+ T cells and decreased concentrations of serum CD25 and TNFR2 were also associated with initial response.65 In addition, a combination of T‐cell receptor CD25 suppression and a decrease in IL‐5 secretion was predictive of treatment response with 85% accuracy.66 Reduction in tenascin C (an extracellular matrix glycoprotein) predicted downregulation of CCL2 (a proinflammatory chemokine), which was associated with response at week 14.57 Nonresponders to anti‐TNF dose intensification had high IL‐6 and sTNFR2 compared to responders.67 In UC, anti‐TNF nonresponse was associated with high baseline TNF, IL‐1β, IL‐10 and IFN‐γ, and decreased TNF, IL‐1β, IL‐6 and IL‐10 production upon peripheral blood mononuclear cell stimulation in vitro.68 The TNF/CRP ratio was associated with clinical response (OR 2.8 [1.4‐5.5], P = 0.003), which may underscore the contribution of TNF‐independent inflammation. An elevated IL‐8 concentration at baseline was also associated with nonresponse.69 Finally, a decrease in serum IL‐9 between baseline and week 14 could accurately predict both clinical remission and mucosal healing at week 30 (AUC 0.803 and 0.752 respectively).70 Vitamin D Vitamin D deficiency (<30 ng/mL) predicted earlier cessation of anti‐TNF therapy (HR 2.13 [1.03‐4.39], P = 0.04).71 Severe vitamin D deficiency (<20 ng/mL) was linked with ANA seropositivity (OR 6.015 [1.054‐51.599]), which was in turn associated with anti‐TNF failure (adjusted OR 20.107 [2.101‐192.388]).72 Conversely, an association between low baseline vitamin D concentration and improved clinical anti‐TNF response was recently reported (80% vs 23%; OR 3.5 [1.3‐99.7]).73 Microbial biomarkers As previously described, ANA seropositivity has been associated with anti‐TNF failure.72 In addition, a significantly larger proportion of pANCA negative CD patients achieved clinical response as compared to pANCA positive patients.39 In a multivariable analysis, pANCA+/ASCA‐ status was the only independent predictor of failure to achieve early clinical response to infliximab in UC patients (OR 0.4 [0.16‐1.00], P = 0.049).74 Similarly, pANCA seronegativity in UC patients was associated with early clinical anti‐TNF response in UC patients (P = 0.037). However, the likelihood of achieving clinical remission was not significantly increased (P = 0.557).52 Furthermore, anti‐OmpC status was associated with both anti‐TNF response (OR 0.14 [0.03‐0.6], P = 0.04) and therapy discontinuation at 1 year (HR 2.2 [1.1‐4.7], P = 0.03).75 Finally, low baseline IFI16 IgG level was associated with clinical response to infliximab induction treatment (OR 0.143 [0.027‐0.761]).76 Albumin, haemoglobin, CRP and neutrophil‐to‐lymphocyte ratio The value of albumin,61, 77 haemoglobin78, 79 and CRP40, 77-83 for predicting anti‐TNF response has been reported in several studies (Table S7). Evidence from one study suggests that baseline neutrophil‐to‐lymphocyte ratio predicts secondary loss of response to IFX treatment in UC patients (HR 3.86 [1.20‐12.4], P = 0.023; AUC 0.798).84 Faeces An overview of faecal biomarkers as predictors of therapeutic response is presented in Table S3. In acute severe UC, nonresponse to IFX (as defined by the need for colectomy during admission) was associated with higher faecal calprotectin (FC) values at time of hospitalisation (1795 µg/g vs 920 µg/g, AUC 0.77, P = 0.06).85 Conversely, in UC patients treated with ADA, high pre‐treatment FC values were shown to be associated with sustained clinical and endoscopic response at week 52 (585.5 µg/g [300‐689] vs 372 µg/g [232.5‐450.5], P = 0.049).88 A steep decrease in FC between baseline and week 2 could predict endoscopic remission at week 10 (P < 0.01; β = 0.7 [0.27‐1.12]).89 Week two concentrations of FC (AUC 0.82 and 0.61), faecal lactoferrin (AUC 0.84 and 0.80) and the dimeric M2 isoform of pyruvate kinase (AUC 0.88 and 0.78) could accurately predict both clinical and endoscopic response to IFX induction treatment.90 Finally, several authors have reported the association between low post‐induction FC levels and the decrease between baseline and post‐induction FC values and subsequent sustained response.90-93 3.1.4 Microbiota High baseline abundance of Bifidobacterium, Clostridium colinum, Eubacterium rectale, uncultured Clostridiales and Vibrio, together with a lower abundance of Streptococcus mitis, predicted response to anti‐TNF therapy in one study (Table S4).94 Recently, a lower baseline dysbiosis index and higher abundance of Faecalibacterium prausnitzii were associated with subsequent clinical and endoscopic response, however these findings lacked statistical significance.95 3.2 Anti‐integrins (VDZ// etrolizumab (ETZ)) Three studies reported on predictive biomarkers for therapeutic response to anti‐integrins (Tables 5 and S6 and Figure 3).96-101 In ETZ‐treated patients, higher mucosal baseline levels of granzyme A mRNA and integrin αE mRNA were associated with clinical remission and mucosal healing. Patients with high, compared to low, granzyme A mRNA had significantly increased CCL5 and decreased CXCL1—proteins implicated in the recruitment of memory T cells—at baseline.97 Baseline mucosal integrin α4β7 expression has been linked to subsequent VDZ response with contradictory findings. High integrin α4β7 expression on both T‐ and B‐cell subsets was associated with subsequent VDZ response in IBD patients (P = 0.0047).99 Conversely, low numbers of baseline integrin α4β7 expressing T lymphocytes were also associated with clinical response to VDZ in UC (n = 17), however, not in CD.100 At the microbiome level, high baseline α‐diversity, an abundance of butyrate‐producing species (including Roseburia inulinivorans and Burkholderiales) and increased branched chain amino acid synthesis were associated with clinical response to VDZ at week 14. With an AUC value of 0.872, the optimal neural network prediction model (which incorporates both clinical and microbial variables) accurately predicted treatment response.101 Reference (year) Response definition Biomarker Association Predictive value Gene expression and proteins Fuchs (2017) UC: Clin Resp: MCS (mayo clinical subscore) decrease ≥2 at W16 α4β7 expression at baseline α4β1 expression on CD4+ Tcells at W6 predicts W16 Clin Resp Clin Resp lower expression P < 0.01,No quant pred data cut‐off +4,2%, Sens 100%, Spec 100% P < 0,01 Tew (2016) Clin Rem: total Mayo Clinic Score ≤2, no individual subscore >1. Endo Rem: MH (=Endo score≤1) BL higher level of granzyme A mRNA BL higher level of integrin αE mRNA Clin Rem Endo Rem PPV/NPV (all pts) 41%/94%; (aTNF‐naïve) 75%/88% P < 0.05 Not specified Proteins Boden (2018) Endo Resp: improvement from BL moderate/severe to mild inflammation or reduction extent >50%. Clin Resp: decrease HBI or SSCAI ≥3 or ≤3 within 180 days higher pre‐treatment α4β7 expression Endo&Clin Resp multiple subsets of T, B, and NK cells, with terminal effector memory (mean CD4: 41% ± 2.6% vs 25% ± 3.3%, P = .0009, mean CD8: 43% ± 3.5% vs 28% ± 3.2%, P = .0043) and NK cells (mean =34% ± 3.2% vs 17% ± 4.4%, P = .0047) Stallmach (2016) SFCR at W30 and W54. (Clin Rem: CD: HBI ≤4; UC: pMayo≤1 with RB subscore of 0 at W54) Lower FC (W14) Lower CRP (W14) SFCR SFCR median 354vs3000µg/kg P = 0.002,No quant pred data P = 0.003, No quant pred data Intestinal microbiota Ananthakrishnan (2017) CD: Clin Rem: HBI<4, Clin Resp: decrease HBI>3. UC: Clin Rem: SSCAI<2, Clin Resp: decrease SSCAI>3. Manually curated list of 40 microbiome variables Community alpha‐diversity at baseline Community beta‐diversity at baseline Roseburia inulinivorans and Burkholderiales species 13 pathways, including branched chain amino acid biosynthesis pathways Clin Rem Clin Rem Clin Rem Clin Rem Clin Rem AUC 0,872, >80% true pos <25% false neg α diversity sign higher (q < 0.1), β diversity sign lower, higher BL(q = 0,0914, q = 0,0614) significantly enriched, CD: Crohn's disease; UC: ulcerative colitis; W: weeks; BL: baseline; HBI: Harvey Bradshaw Index; Clin: clinical; Endo: endoscopic; Rem: remission; Resp: response; SFCR: steroid free clinical remission; RB: rectal bleeding; MH: mucosal healing; FC: faecal calprotectin; CRP: C‐reactive protein; PPV: positive predictive value; NPV: negative predictive value; sign: significant; No quant pred data: No quantitative predictive data. 3.3 Anti‐IL23 Thus far, no studies have explored molecular markers as predictors of response to ustekinumab. However, a recent phase 2a CD study of a selective anti‐IL23p19 antibody demonstrated that a significantly higher proportion of patients with elevated baseline IL‐22 serum concentration achieved clinical response and remission at week 8 compared to patients with low IL‐22 levels.102 So far, this observation has not been confirmed with other p19 inhibitors. 3.4 Immunomodulators Despite an abundance of observational studies examining the relationship between molecular markers and adverse events related to immunomodulator use in IBD, evidence regarding biomarkers as predictors of treatment efficacy are scarce (Table S5 and Figure 3).15, 19-21, 103-105 Homozygous carriers for IL23R‐G9T were more likely to respond to azathioprine therapy.15 Moreover, the Rac1 SNP (rs34932801) genotype GC was associated with lower rates of clinical response compared to the wild type (46% vs 76%; OR 0.26 [0.08‐0.91], P = 0.036).20 However, these results could not be replicated in a paediatric IBD population.104 A complete deletion of the GSTM1 gene (glutathione S‐transferase) was associated with poor clinical response to thiopurine treatment (OR 9.22 [1.018‐78.62], P = 0.042).105 Furthermore, a BMI <25 kg/m2 (HR 3.95 [1.55‐5.83], P = 0.001) and albumin concentration <4 g/dL (HR 1.98 [0.97‐4], P = 0.06) were associated with thiopurine failure.103 No studies of methotrexate met the pre‐defined inclusion criteria.
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Research ArticleGastroenterologyImmunology Free access | 10.1172/JCI120453 Interaction between smoking and ATG16L1T300A triggers Paneth cell defects in Crohn’s disease Ta-Chiang Liu,1 Justin T. Kern,1 Kelli L. VanDussen,1 Shanshan Xiong,1 Gerard E. Kaiko,1 Craig B. Wilen,1 Michael W. Rajala,2 Roberta Caruso,2 Michael J. Holtzman,3 Feng Gao,4 Dermot P.B. McGovern,5 Gabriel Nunez,2 Richard D. Head,1 and Thaddeus S. Stappenbeck1 First published August 23, 2018 - More info Related article: Abstract It is suggested that subtyping of complex inflammatory diseases can be based on genetic susceptibility and relevant environmental exposure (G+E). We propose that using matched cellular phenotypes in human subjects and corresponding preclinical models with the same G+E combinations is useful to this end. As an example, defective Paneth cells can subtype Crohn’s disease (CD) subjects; Paneth cell defects have been linked to multiple CD susceptibility genes and are associated with poor outcome. We hypothesized that CD susceptibility genes interact with cigarette smoking, a major CD environmental risk factor, to trigger Paneth cell defects. We found that both CD subjects and mice with ATG16L1T300A (T300A; a prevalent CD susceptibility allele) developed Paneth cell defects triggered by tobacco smoke. Transcriptional analysis of full-thickness ileum and Paneth cell–enriched crypt base cells showed the T300A-smoking combination altered distinct pathways, including proapoptosis, metabolic dysregulation, and selective downregulation of the PPARγ pathway. Pharmacologic intervention by either apoptosis inhibitor or PPARγ agonist rosiglitazone prevented smoking-induced crypt apoptosis and Paneth cell defects in T300A mice and mice with conditional Paneth cell–specific knockout of Atg16l1. This study demonstrates how explicit G+E can drive disease-relevant phenotype and provides rational strategies for identifying actionable targets. Introduction Subtyping of complex immune diseases, such as inflammatory bowel disease (IBD), has traditionally been done by categorizing clinical phenotypes and disease presentations (1, 2). Incorporating key pathogenic elements, namely genetic susceptibility and relevant environmental exposure (G+E) (3), into subclassification schemes may facilitate identification of therapeutic targets in these subtypes. The identification of more than 200 susceptibility SNPs and recently identified prognosis-associated SNPs (4, 5) for Crohn’s disease (CD), one major form of IBD, poses a challenge to this approach, as many of these SNPs have been associated with gene expression and functional changes in various cell types, such as immune (6–9) and epithelial cells (10, 11). While development of gene scores has shown promise in subtyping patients (12), such scores do not account for environmental exposures that are likely to trigger phenotypes and disease. Likewise, environmental factors identified by epidemiologic studies require relevant and functional testing in preclinical models where exposure to these environmental factors is controlled. Conversely, environmental factors identified in preclinical models need to be confirmed in patients. Development of a surrogate phenotype/biomarker that can integrate the effects from both genetics and environmental factors will facilitate subtyping of IBD. In CD, morphologic patterns of small intestinal Paneth cells (Paneth cell phenotype) are a surrogate phenotype that stratifies CD into prognostically distinct subtypes (13–15). We and others have shown that, in mouse models, knockout of CD-associated genes (Atg16l1, Xbp1, Irgm, Lrrk2) resulted in Paneth cell defects manifested as secretory granule abnormalities (11, 16–18) that are similar to those observed in CD subjects (11, 14, 15), with potential additive effects between genes (14). We previously showed that administration of a chronic strain of murine norovirus (MNV) could induce Paneth cell defects in Atg16l1HM (hypomorph) mice, which express low levels of Atg16l1 protein (19). In human subjects, Paneth cell defects in CD are associated with microbiota changes (20) and poor clinical outcome (14, 15). Thus, Paneth cell phenotypes are biologically and clinically relevant surrogate phenotypes ideally suited for mechanistic studies and identification of potential therapeutics in CD. One G+E trigger for Paneth cell defects in mouse models, MNV (19), as yet has no correlate in human subjects (21, 22). Therefore, our goal was to identify an environmental trigger for Paneth cell defects that occurs in both CD subjects and analogous mouse models. Among the known CD environmental risk factors (1, 23), cigarette smoking is one of the most reproducible (23, 24). It is also associated with an aggressive disease course in patients with established CD (25). A recent study suggested potential interactions between genetics and cigarette smoking (26). Based on these findings, we hypothesized that smoking would induce Paneth cell defects in genetically susceptible CD patients. As a proof of concept, we investigated the correlation of smoking exposure, Paneth cell defects, and postoperative recurrence after ileal/ileocolonic resections in CD subjects with ATG16L1T300A, the most prevalent CD susceptibility SNP in White patients (4). We then performed functional studies using the Atg16l1T300A mouse model to identify host factors that mediated smoking-induced Paneth cell defects. Finally, we validated rationally designed therapeutic strategies targeting these factors that result in Paneth cell defects. Results CD subjects with ATG16L1T300A were susceptible to smoking-associated Paneth cell defects. We found that in CD subjects (demographics described in Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/JCI120453DS1) who received ileocolonic anastomosis and postoperative immunomodulatory and/or biologics prophylactic therapy (a known confounder for outcome; n = 128), smoking status and Paneth cell phenotype were prognosticators of recurrence (Supplemental Figure 1) and the combination of these factors further stratified patients into prognostically distinct subgroups (Figure 1A). In addition, CD subjects who were of the ATG16L1T300A genotype and who were also smokers (T300A-smoking group) showed significantly shorter time to recurrence after surgery (Supplemental Figure 2). We therefore hypothesized that cigarette smoking was a trigger for Paneth cell defects in CD subjects. Given that the most common risk allele for CD susceptibility known to be associated with Paneth cell defects was ATG16L1T300A (11), we further hypothesized that smoking triggers Paneth cell defects preferentially in CD subjects who harbored the ATG16L1T300A risk allele(s). In support of this hypothesis, the ATG16L1T300A genotype in CD subjects who were smokers was associated with a lower percentage of normal Paneth cells, whereas subjects with no-risk (NR) allele were not (Figure 1, B and C, and Supplemental Table 2). We have previously described several distinct classes of abnormal Paneth cell morphology (14, 27). We determined the distribution of each subclass of abnormal Paneth cells and found that the majority of the abnormal Paneth cells were of the D2 subclass (decreased granules) (Supplemental Figure 3); this was similar to previous findings in adult CD (14, 15, 27). None of the individual abnormal morphology subclasses showed a significantly different distribution across the groups; rather, the sum percentage of these abnormal classes (or conversely, the percentage of normal Paneth cells) provided the most robust association in the T300A-smoking group (Figure 1C). Figure 1 CD subjects with ATG16L1T300A genotype (T300A) were more susceptible to cigarette smoking–associated Paneth cell defects. (A) In a cohort of CD subjects (n = 186) who underwent ileocolectomy, 126 received postoperative prophylaxis. Within this prophylaxis subset, smokers with type I Paneth cell phenotype (<80% Paneth cells with normal granule morphology) showed the shortest time to disease recurrence (P = 0.0183 by log-rank test). (B) Representative HD5 immunofluorescence. Scale bar: 10 μm. Asterisks indicate abnormal Paneth cells. (C) Cigarette smoking was associated with lower percentage of normal Paneth cells in patients with ATG16L1T300A allele or alleles, while no significant differences in Paneth cell defects were seen between NR patients with or without smoking history (overall P =0.001). NR-nonsmoking, n = 25; NR-smoking, n = 14; T300A-nonsmoking, n = 84; T300A-smoking, n = 62. Data were analyzed by Kruskal-Wallis test followed by Dunn’s multiple comparison tests between groups and represent mean ± SEM. P values for comparisons between groups are shown in Supplemental Table 2. *P < 0.05; **P < 0.01. Given that NOD2 is the other CD susceptibility gene known to be associated with Paneth cell defects in North American CD cohorts (14), we also examined the correlation among common NOD2 variant (R702W, G908R, and L1007fs) carrier status, smoking status, and Paneth cell phenotype. There were no significant changes in the percentage of normal Paneth cells in subjects carrying NOD2 variants that were smokers (Supplemental Figure 4A). We further correlated the total numbers of ATG16L1T300A and NOD2 risk alleles, smoking status, and Paneth cell phenotype. There was no significant difference in the genetic burden regarding Paneth cell phenotype and smoking status (Supplemental Figure 4B). Therefore, smoking-induced Paneth cell defect correlated specifically with ATG16L1T300A alleles in this cohort. Atg16l1T300A mice were susceptible to smoking-induced Paneth cell defects. We modeled the 4 patient populations above in a mouse model representative of the G+E interactions by exposing Atg16l1T300A mice (28) and WT littermates to cigarette smoke for 4 weeks (Figure 2A). Paneth cell defects were triggered only in the Atg16l1T300A mice (Figure 2B and Supplemental Table 3), recapitulating the findings in CD subjects. We also examined the distribution of each class of abnormal Paneth cells. In observations similar to those in the human cohort, the abnormal Paneth cells were predominantly of the D2 subclass, with a small percentage of D3 subclass (diminished) (Supplemental Figure 5A). Increased percentages of these 2 subclasses of abnormal Paneth cells were largely responsible for the decreased percentage of normal Paneth cells in the T300A-smoking group (Supplemental Figure 5, B–D). Figure 2 Atg16l1T300A mice were more susceptible to Paneth cell defects after exposure to cigarette smoking. (A) Schematic illustration of experimental design. Atg16l1T300A (T300A) mice and WT littermates were treated with or without cigarette smoking for 4 weeks, and Paneth cell morphology was assessed. (B) Smoking induced more Paneth cell defects, specifically in Atg16l1T300A mice (overall P < 0.0001). (A and B) WT-nonsmoking, n = 12; WT-smoking, n = 21; T300A-nonsmoking, n = 19; T300A-smoking, n = 25. Results are from 6 independent experiments. Data were analyzed by 2-way ANOVA. (C) Two weeks of cigarette smoking was sufficient to induce Paneth cell defects in Atg16l1T300A mice (P = 0.0054), while no additional Paneth cell defects were seen with longer exposure time, up to 6 weeks (P > 0.9999). Nonexposed, n = 17; 2 weeks, n = 10; 4 weeks, n = 10. (D) After 4 weeks of cessation of cigarette exposure, the percentage of normal Paneth cells of the Atg16l1T300A mice returned to a level comparable to that of unexposed status (P = 0.0027). Baseline, n = 6; 2 weeks, n = 7; 4 weeks, n = 7. (C and D) Data were analyzed by 1-way ANOVA, followed by Mann-Whitney U tests between groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. (B–D) Data represent mean ± SEM. We also performed transmission electron microscopy (TEM) to investigate potential ultrastructural changes in Paneth cells. We found that Paneth cells of the T300A mice contained cytoplasmic vesicles and degenerative mitochondria (Supplemental Figure 6, A–C), which was similar to our previous observations in Atg16l1HM mice (11). Importantly, these changes were more frequent in T300A mice exposed to smoking compared with those that were not (Supplemental Figure 6D). Paneth cells from CD patients that were of the ATG16L1T300A genotype and smokers also possessed similar features (Supplemental Figure 6, E and F). To exclude the possibility that the Paneth cell defects in the T300A-smoking mice were the result of stress associated with the physical presence in the smoking chamber rather than exposure to cigarette smoke, T300A mice were placed in the smoking chamber and exposed to normal air pumped through the machine (i.e., no exposure to cigarette smoke). Physical presence in the smoking chamber alone with exposure to normal air did not result in Paneth cell defects in these mice (Supplemental Figure 7). We next altered the duration of smoking to determine the impact on Paneth cell phenotypes. We found that a 2-week exposure was sufficient to trigger Paneth cell defects in Atg16l1T300A mice, but that exposure beyond 2 weeks did not increase the percentage of defective Paneth cells (Figure 2C). We also tested the durability of smoking-induced Paneth cell defects. Paneth cell phenotype was examined in Atg16l1T300A mice at the end of a 4-week smoking period (baseline), followed by a 2- or 4-week washout period where smoking was discontinued. Four weeks of washout (but not 2 weeks) were required to restore normal Paneth cell morphology (Figure 2D). Therefore, Paneth cell defects in Atg16l1T300A mice after short-term smoking exposure were reversible upon smoking cessation. We also determined whether administration of nicotine, a major component in cigarettes, would elicit similar effects on Paneth cells. We administered a daily dose of nicotine (0.7 mg/mouse/d) to mice instead of cigarette smoke. This dose is greater than the predicted absorbed nicotine dose (approximately 0.42 mg/mouse/d) achieved in the cigarette-smoking experiments based on the nicotine content of the cigarettes and known absorption kinetics (29, 30). Surprisingly, nicotine administration did not induce Paneth cell defects or crypt base apoptosis in Atg16l1T300A mice (Supplemental Figure 8). Gut microbiota did not alter smoking-induced Paneth cell defects. Paneth cell function is important for maintaining the homeostasis of the gut microbial community (31–33), and dysbiosis can develop as a downstream effect of Paneth cell defects or loss (20, 34, 35). Thus, we examined whether microbiota changes occurred upstream of or as part of a feedback loop with Paneth cell defects in the context of G+E. We first compared the microbial compositions in Atg16l1T300A mice and littermates with and without smoking. There was no significant difference in microbial composition between Atg16l1T300A mice and littermates without smoking (Supplemental Figure 9A). Smoking did not result in significant changes in α (Supplemental Figure 9, B and C) or β diversity (Supplemental Figure 9, D and E) in either Atg16l1T300A mice or littermates. Deeper examination of specific microbial taxa showed only limited differences between the groups of mice. For example, smoking induced relatively increased abundance of Lactobacillales and Turicibacterales and reduced the abundance of Alphaproteobacteria and Betaproteobacteria in Atg16l1T300A mice, whereas it only increased the abundance of Coriobacterales and Turicibacterales in the WT littermates (Supplemental Figure 9, F and G). Therefore, smoking only modestly altered the composition of the gut microbiota, regardless of genotype. Because we did detect small differences in the microbiota composition that depended on smoking in Atg16l1T300A mice, we functionally tested the microbiota for its ability to induce Paneth cell defects. We cohoused Atg16l1T300A mice and WT littermates exposed to smoking (microbiota donors) with mice of the same genotypes not exposed to smoking (microbiota recipients) (Figure 3A). Recipients were pretreated with antibiotics (36) to allow successful colonization of donor microbiota. The recipients showed microbiota compositions indistinguishable from those of their respective donors after 4 weeks (Supplemental Figure 10). Cohousing of donors and recipients did not induce Paneth cell defects in Atg16l1T300A recipients (Figure 3B). Therefore, the limited differences in microbial composition observed with smoking in the Atg16l1T300A mice did not contribute to Paneth cell defects. Figure 3 Smoking-associated Paneth cell defects in Atg16l1T300A mice were not horizontally transmissible by cohousing. (A) Schematic illustration of experimental design. Smoking Atg16l1T300A mice and WT littermates were used as microbiota donors and cohoused with nonsmoking, antibiotic-pretreated mice of the same genotypes as recipients. Cohousing lasted 4 weeks, during which the donors continued to receive exposure to cigarette smoking. (B) The Paneth cell defects of the Atg16l1T300A microbiota donor mice did not transfer to recipient mice. WT donors, n = 5; WT recipients, n = 15; T300A donors, n = 5; T300A recipients, n = 17. Data analyzed by Kruskal-Wallis test followed by Dunn’s multiple comparison tests between groups. *P < 0.05; **P < 0.01. Data represent mean ± SEM. Smoking-induced Paneth cell phenotype did not correlate with lung or systemic inflammation. To determine whether Paneth cell defects could be due to secondary changes of lung and/or systemic inflammation, we further examined the lungs for histopathology and serum for inflammatory markers. No overt inflammation was seen in the lungs in any of the mice (Supplemental Figure 11), consistent with a previous report that longer smoking exposure may be required to elicit lung inflammation (37). Likewise, none of the samples showed detectable TNF-α in serum (Supplemental Figure 12A). In addition, there was no significant difference in serum myeloperoxidase, RAGE, CXCL1, CXCL2, IL-6, or IL-1β levels among the groups (Supplemental Figure 12, B–G). Therefore, there was no correlation between lung or systemic inflammation and G+E-associated Paneth cell defects. Natural MNV infection was an unlikely cause for smoking-induced Paneth cell defects. We previously showed that administration of a chronic strain of MNV could induce Paneth cell defects in Atg16l1HM mice (19). To exclude the possibility that natural MNV infection, not infrequently encountered in animal facilities (19), could result in Paneth cell defects in Atg16l1T300A mice exposed to smoking, we also determined the MNV titers in fecal samples. We found that 16% of mice were indeed infected with MNV. However, among the Atg16l1T300A mice exposed to smoking, there was no significant difference in the percentages of normal Paneth cells between MNV-uninfected and MNV-infected mice (Supplemental Figure 13). Therefore, natural MNV infection was an unlikely cause for the Paneth cell defects observed in this study. Smoking and Atg16l1T300A genotype interaction led to unique host transcriptomic changes. The lack of a causative link among the microbiota, systemic inflammatory markers, and Paneth cell defects indicates that the underlying mechanisms most likely stemmed from the host intestine per se. To comprehensively analyze the effect of G+E in all ileal cell types, we performed global RNA sequencing (RNA-seq) using mRNAs isolated from full-thickness ileal sections from Atg16l1T300A mice and WT littermates with or without smoking. Identified transcriptomic differences were categorized as associated with either genetics (G patterns), smoking (E patterns), or combinatorial effects of genetics and smoking (G+E patterns) (Supplemental Figure 14A). The G+E patterns could be further classified into T300A-smoking and WT-smoking patterns (Figure 4, A and B, and Supplemental Figure 13, B–E). The T300A-smoking pattern was striking, as it included signatures associated with the promotion of apoptosis and the downmodulation of insulin signaling, predominantly through Ppara/g regulation (Figure 4A, Supplemental Figure 14, B–E, and Supplemental Table 4). Interestingly, Pparg activity has been shown to modulate Paneth cell function during high-fat–diet exposure (38). Figure 4 G+E interactions resulted in unexpected transcriptomic findings. Unique transcriptomic patterns associated with (A and B) combination from both genetics and smoking interactions (G+E patterns), (C) genetics alone (G patterns), or (D) smoking exposure alone (E patterns). Full-thickness ileum from Atg16l1T300A mice and WT littermates with or without cigarette smoking exposure was analyzed by RNA-seq. The x axes in all panels represent log P values. Significantly enriched pathways are shown. The WT-smoking pattern included induction of genes associated with Hnf4α and Ppar regulation in addition to lipid and amino acid metabolism (Figure 4B, Supplemental Figure 14F, and Supplemental Table 5). These molecular responses to smoking were either attenuated or not activated in the Atg16l1T300A mice. The G patterns specific to the Atg16l1 T300A ileum included genes that function in metabolism and complement activation (Figure 4C, Supplemental Figure 14, G and H, and Supplemental Table 6). We had previously found that deletion of Atg16l1 in mouse intestinal epithelial cells targets metabolism and acute-phase reactants such as complement (11). The E patterns enriched with smoking included genes that function in cell death, IFN signaling, cyclooxygenase pathway, and gluconeogenesis (Figure 4D, Supplemental Figure 14, I and J, and Supplemental Tables 7 and 8). Of note, smoking can induce apoptosis in a mouse model of emphysema (39). Apoptosis was a central mechanism behind smoking-associated Paneth cell defects in CD subjects and mice with ATG16L1T300A. The analysis of the transcriptomics data suggested that apoptosis-associated cell death might be a critical mediator of G+E-induced Paneth cell defects. We found that in CD subjects, the highest level of crypt base apoptosis was present in Atg16l1T300A-smoking as compared with all other groups (Figure 5A, Supplemental Figure 15A, and Supplemental Table 2). Further analysis showed that Paneth cells themselves were sensitive to apoptosis in ATG16L1T300A-smoking through defensin 5 (HD5)/TUNEL colocalization (Figure 5B and Supplemental Table 2). In addition, ATG16L1T300A-smoking, but not NR-smoking, also had lower Paneth cell numbers/crypt (Figure 5C and Supplemental Table 2). The effects of smoking and genotype showed no detectable effect on crypt proliferation, the other major function of epithelial cells in the crypt base (Supplemental Figure 16, A and B, and Supplemental Table 2). Figure 5 Paneth cell defects were mediated by apoptosis. (A) Smoking was associated with more crypt base apoptosis in CD subjects with the Atg16l1T300A genotype (P < 0.0001), compared with NR subjects (P > 0.9999). (B) Smoking was associated with more apoptotic Paneth cells in CD subjects with ATG16L1T300A (P = 0.01) compared with NR subjects (P > 0.9999). (C) ATG16L1T300A subjects who were smokers had reduced Paneth cell numbers/crypt (P = 0.0103) compared with NR subjects (P > 0.9999). (A–C) Sample sizes and data analysis were as in Figure 1. (D) In mice, smoking induced more profound crypt base apoptosis specifically in Atg16l1T300A mice (P < 0.0001). (E) More Paneth cells were undergoing apoptosis in Atg16l1T300A mice exposed to cigarette smoking (P = 0.0018). (F) Smoking did not induce significant alterations in Paneth cell numbers/crypt, irrespective of genotype (P = 0.0948). (G) Smoking did not induce increased apoptosis in the villi, irrespective of genotype (P = 0.5058). (D–G) Sample sizes and data analysis were as in Figure 2. Pan-caspase inhibitor Z-VAD-FMK administration prevented smoking-induced (H) Paneth cell defects and (I) crypt base apoptosis in Atg16l1T300A mice. (H and I) Control, n = 8; pan-caspase inhibitor, n = 10; nonsmoking, n = 7. Data were analyzed by Kruskal-Wallis tests followed by Dunn’s multiple comparison tests between groups. *P < 0.05; **P < 0.01, ***P < 0.001; ****P < 0.0001. Data represent mean ± SEM. Atg16l1T300A mice exposed to smoking also showed increased crypt apoptosis (Figure 5D, Supplemental Figure 15B, and Supplemental Table 3) and specifically increased Paneth cell apoptosis (Figure 5E and Supplemental Table 3), confirming that apoptosis-associated cell death in the crypt base compartment was directly linked to smoking-induced Paneth cell defects. Of note, the Paneth cells that coexpressed cleaved caspase-3 and lysozyme were exclusively of the abnormal morphology (human: 92% D2, 8% D3; mouse: 97% D2, 3% D3). Atg16l1T300A mice exposed to smoking tended to have fewer Paneth cells as compared with smoking WT littermate controls (WT-smoking), but this was not significant (Figure 5F and Supplemental Table 3). We also found that smoking did not induce apoptosis in villus epithelial cells (Figure 5G and Supplemental Figure 15C), further demonstrating that smoking and genotype specifically affect Paneth cells. Finally, crypt proliferation was not altered by exposing mice of either genotype to smoke (Supplemental Figure 16, C and D, and Supplemental Table 3). Therefore, crypt base apoptosis was a specific response to G+E, and the process did not elicit compensatory alterations in proliferation. To determine whether apoptosis mediated the smoking-induced Paneth cell defects in Atg16l1T300A mice, we administered pan-caspase inhibitor carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]-fluoromethylketone (Z-VAD-FMK) to the Atg16l1T300A mice. Z-VAD-FMK prevented the Paneth cell defects (Figure 5H) and crypt apoptosis (Figure 5I) induced by smoking, confirming that apoptosis is upstream of Paneth cell defects. In addition, we also determined the potential role of necroptosis in mediating Paneth cell defects (40), as a recent report has suggested a link between Atg16l1 and necroptosis (41). Administration of the necroptosis inhibitor nec-1 did not prevent the Paneth cell defect (Supplemental Figure 17A) nor crypt base apoptosis (Supplemental Figure 17B) phenotypes in T300A-smoking mice, confirming the lack of association with necroptosis in this experimental design. Repressed Pparg activation resulted in smoking-induced crypt apoptosis and Paneth cell defects. The unique G+E patterns in the full-thickness ileal transcriptomic analysis demonstrated an attenuation or repression of Ppara/g activation in the Atg16l1T300A mice exposed to smoking as compared with WT animals (Supplemental Figure 14, C–E, Supplemental Table 9). These data suggested the possibility that Ppara/g activation in WT-smoking mice may be protective of the normal Paneth cell phenotype. In a subsequent analysis of the G+E patterns using Enrichr to probe the GEO drug perturbations data sets (refs. 42, 43, and Supplemental Figure 18A), the WT-smoking pattern genes uniquely matched compounds with multiple highly significant adjusted P value entries (adjusted P < 0.01) (Supplemental Figure 18B). The analysis revealed that selective PPARγ agonists, including rosiglitazone, pioglitazone, and troglitazone (especially among the drug-like molecules) regulate the genes in this potentially protective pattern, whereas fibrates (PPARα agonists) were not detected in this analysis. This suggested the general Ppara/g signature observed in the pathway-level analysis may be more specific to Pparg. To further justify analysis of this pathway in Paneth cells, we performed global transcriptional analysis of crypt base material (enriched for Paneth cells) from these mice collected by laser capture microdissection (LCM) (Figure 6A). We found that Atg16l1T300A mice exposed to smoking showed significantly diminished expression of many Pparg-associated genes as compared with the other groups of mice in this experiment (Figure 6B and Supplemental Table 10). We also found a similar enrichment of downregulated PPARγ pathway genes in 2 specific G+E groups from our previous LCM-procured Paneth cell data sets: (a) Atg16l1HM mice infected with MNV (ref. 19, Figure 6B, and Supplemental Table 11), and importantly, (b) CD subjects who were smokers and of the ATG16L1T300A genotype (ref. 14, Figure 6B, and Supplemental Table 12). These data collectively suggest that the PPARγ pathway is a central mechanism closely linked to Paneth cell defects in CD subjects and relevant mouse models as a result of G+E interaction. Figure 6 Pparg-associated metabolism dysregulation resulted in crypt base apoptosis and Paneth cell defects. (A) Workflow for Paneth cell LCM of the mice in the T300A-smoking study. (B) Significantly downregulated Pparg-associated genes were found in all 3 data sets, including the Atg16l1T300A-smoking mice (n = 108 genes), Atg16l1HM MNV-infected mice (n = 298 genes), and CD subjects that were ATG16L1T300A-smokings (n = 166 genes). Adjusted P value for each group (by ChEA, https://omictools.com/chea-tool): #P = 0.0044; ##P = 0.0004; ###P = 0.038. Ppar-γ agonist rosiglitazone (Rosi) treatment rescued (C) Paneth cell defects (P < 0.0001) and (D) crypt base apoptosis (P < 0.0001) in Atg16l1T300A mice exposed to cigarette smoking. (C and D) Total n = 9/group for nonsmoking groups; n 0/group for smoking groups. Rosiglitazone administration prevented the (E) Paneth cell defects and (F) crypt apoptosis of PC-Cre+ smoking mice (n = 4/group). (C–E) Statistical analysis was performed using 2-way ANOVA. *P < 0.05, ****P < 0.0001. Data represent mean ± SEM. We next functionally tested the role of the PPARγ pathway in smoking-induced Paneth cell defects. Administration of the PPARγ agonist rosiglitazone rescued the smoking-induced Paneth cell defects (Figure 6C) and crypt base apoptosis (Figure 6D) in the Atg16l1T300A mice. In parallel, we also generated mice with intestinal epithelium–specific Pparg deletion (Pparg/Villin-Cre mice). These mice showed reduced percentages of normal Paneth cells, reduced Paneth cell numbers/crypt, and increased crypt base apoptosis compared with the Ppargfl/fl littermate controls (Supplemental Figure 19). Therefore, the PPARγ pathway is a critical mediator of crypt apoptosis and Paneth cell defects. G+E interactions directly affected Paneth cells and precursors. The crypt base transcriptomic data also suggested that the G+E interaction induced effects directly on Paneth cells themselves. To test this hypothesis in vivo, we utilized a conditional knockout model in which Atg16l1 was deleted exclusively in Paneth cells (α-defensin-4-IRES-Cre Atg16l1fl/fl mice; herein termed PC-Cre+ mice) (44). As seen in Supplemental Figure 20A, the PC-Cre+ mice elicited Paneth cell defects when exposed to cigarette smoking, whereas Atg16l1fl/fl mice (herein termed PC-Cre– mice) did not, as expected. The PC-Cre+ mice also showed increased crypt base apoptosis (Supplemental Figure 20B) and increased Paneth cell apoptosis (Supplemental Figure 20C). Finally, rosiglitazone administration also prevented smoking-induced Paneth cell defects and crypt apoptosis in PC-Cre+ mice (Figure 6, E and F). These data further support the notion that the G+E effect can act directly on Paneth cells and their Defa4-expressing precursors, although we cannot exclude Paneth cell–independent mechanisms with certainty. TNF antagonism rescued smoking-induced Paneth cell defects. We previously suggested that TNF-α, a major therapeutic target in CD, may be an important mediator of Paneth cell defects in CD subjects (15). We have also shown that anti–TNF-α treatment can ameliorate the intestinal pathology in Atg16l1HM mice infected with MNV and treated with dextran sodium sulfate (DSS) (19). Interestingly, it has also been shown that PPARγ antagonism in preadipocytes conferred increased sensitivity to TNF-α–induced apoptosis (45) and that treatment with PPARγ agonist blocked TNF-α–induced apoptosis in vitro (46), suggesting that a defective PPARγ pathway could prime the host tissue to TNF-α–induced apoptosis. In Atg16l1T300A mice, anti–TNF-α treatment prevented Paneth cell defects (Figure 7A) and crypt apoptosis (Figure 7B). Anti–TNF-α administration did not alter the expression of genes involved in the PPARγ pathway (Supplemental Figure 21), suggesting that TNF-α acts downstream of PPARγ and mediates apoptosis induction. We further tested the role of TNF-α by crossing Atg16l1T300A mice to TNF receptor 1–deficient (Tnfr1–deficient) mice. Atg16l1T300A Tnfr1–/– mice were resistant to smoking-induced Paneth cell defects (Figure 7C) and crypt base apoptosis (Figure 7D). Therefore, the TNF-α–signaling pathway is a key mediator and therapeutic target for smoking-induced crypt apoptosis and Paneth cell defects in Atg16l1T300A mice. Figure 7 Anti–TNF-α prevented Paneth cell defects. Administration of anti–TNF-α prevented smoking-induced (A) Paneth cell defects (P < 0.0001) and (B) crypt base apoptosis (P = 0.0011) in Atg16l1T300A mice. (A and B) Control, n = 9; anti–TNF-α, n = 10. Compared with the Atg16l1T300A mice, Atg16l1T300A Tnfr–/– mice exposed to cigarette smoking showed significantly (C) fewer Paneth cell defects (P = 0.0022) and (D) less crypt base apoptosis (P = 0.0087). (C and D) n = 6/group. Data were analyzed by Mann-Whitney U test. **P < 0.01; ****P < 0.0001. Data represent mean ± SEM. Discussion We previously showed that Paneth cell phenotypes are associated with CD genotypes, microbiota composition, a pathologic hallmark, unique transcriptomic profiles, and clinical outcome (11, 14, 15, 19, 20). However, clinically relevant environmental trigger or triggers and the mechanism or mechanisms driving Paneth cell defects were unclear (Figure 8A). In the current study, we show that relevant environmental stimuli can trigger Paneth cell defects in genetically susceptible hosts, confirming this phenotype as a unique readout to functionally test potential genetic and environmental interactions. We also show that the G+E interactions resulted in previously unpredicted intestinal metabolic dysregulation, leading to crypt base apoptosis and Paneth cell defects mediated by PPARγ that could additionally be blocked by anti–TNF-α (Figure 8B). Finally, we show that the G+E interactions directly affect Paneth cells and their Defa4-expressing precursors, although other cell types may also be affected. The Paneth cells that underwent apoptosis were exclusively of the abnormal morphology patterns. Therefore, the abnormal Paneth cells may undergo apoptosis; however, they may also revert to normal morphology once smoking is discontinued. Figure 8 Previous and current models of G+E resulting in Paneth cell defects. (A) Previous knowledge suggests G+E interaction may lead to Paneth cell defects, but the mechanisms have been unclear. (B) Proposed mechanistic model based on the current study. Clinically relevant genetic and environmental factors of CD could interact and induce metabolism dysfunction (defective PPARγ signaling), leading to TNF-α–mediated crypt base apoptosis and Paneth cell defects. We focused on Atg16l1T300A, as a knockin model that possesses the same polymorphism as CD patients, providing a mechanistic advantage over the whole gene–knockout models in select cell types. Similar mouse models for Nod2 polymorphisms exist, but this allele is much less common in CD cohorts of European ancestry (4). Other CD susceptibility genes associated with abnormal Paneth cells do not yet have mouse models of their respective genetic polymorphisms. In addition, while we have previously shown that Paneth cell defects are induced in hypomorphic Atg16l1 mice after MNV infection, we are unable to yet identify such a link in CD patients (21). Even so, smoking is a clinically relevant environmental trigger (23, 47). We show that the combination of relevant host genetic and environmental factors can provide insight into disease pathogenesis and therapeutic targets, as has been recently demonstrated in studies such as those of nonalcoholic fatty liver disease (48, 49). The majority of the microbiome studies on the effect of smoking have centered on the oral cavity microbiota (50). A recent population-based microbiome study showed that smoking status and history showed modest effect on Bray-Curtis distance without significant associations for individual species or pathways (51). A small cross-sectional study of CD patients showed that smoking is associated with reduced microbiota diversity, with reduced abundance of limited taxa at the genera level (52). Our in vivo study was consistent with these findings. Along with the failure of horizontal transmission of Paneth cell defects in cohousing experiments, our data strongly suggest that microbiota changes were not a cause of Paneth cell defects. Overall, this supports our working model (53) showing that Paneth cell defects promote dysbiosis only in the presence of active inflammation. In addition, recent studies have suggested that necroptosis modulates Paneth cell function (40, 41). In our study, smoking-induced Paneth cell defects in T300A mice were only rescued by apoptosis inhibition, but not necroptosis inhibition, suggesting that different injuries may elicit different predominant cell death responses. The value of the unbiased global transcriptomics approach is highlighted by the identification of Pparg as a central mediator in the T300A-smoking patterns, a finding that was not deducible from examining the effect of each single factor alone. PPARg has been shown to be downregulated in smoking-associated emphysema (54), suggesting that the modulation of this pathway by smoking is likely a general tissue response. In addition, Pparg is linked to reduced Paneth cell numbers in mice fed a high-fat diet (38). Given that agents targeting this pathway (e.g., rosiglitazone) are readily available for routine clinical use, further clinical studies using these agents to treat CD patients who are smokers with Paneth cell defects will validate the importance of this pathway in CD. Furthermore, metabolic dysregulation is tightly connected with the TNF-α–associated apoptosis pathway. Therefore, previously recognized important genetic factors, an environmental factor, and inflammatory pathways converged to affect Paneth cell health and clinical prognosis. Of note, our complementary approaches (crypt base LCM, PC-Cre+ mice) support the transcriptomics analysis from full-thickness ileum indicating that Paneth cells are the main target of the G+E effect. Our data also suggest that smoking cessation may be beneficial for ATG16L1T300A CD subjects with smoking-associated Paneth cell defects. Other potential intervention approaches include nicotine patch, PPARγ agonists, and anti–TNF-α. Anti–TNF-α is a major treatment modality for CD (1), and rosiglitazone has been shown to be efficacious in ulcerative colitis (another major form of IBD) (55). Our data indicate that the Paneth cell phenotype may be used to stratify CD patients who may benefit from these therapies. One limitation of our study is that, due to the physical restraint of the smoking chamber, the cigarette-smoking experiments could not exceed 6 weeks. Therefore, the effect of long-term cigarette smoking on Paneth cell defects, in particular the reversibility of the approaches described above, is unclear. In addition, while neither nicotine, lung pathology, nor systemic inflammatory signals were shown to affect Paneth cells in this model, it is possible that the changes in gut transcriptomics and subsequent Paneth cell defects are the results of processes initiated external to the diseased/target organ (gut), similar to what occurs in rheumatoid arthritis (56), in which cigarette smoking has been shown to alter transcriptomic changes of the joints (57). One such possibility could be the lung-gut axis, such that cigarette smoking affects the lung on a molecular level (potentially through lung microbiome and/or metabolites) (58, 59), which may in turn affect gut transcriptomics. In addition, the PPARγ pathway has best been studied in liver, skeletal muscle, and adipocytes in the context of metabolism (60). For example, based on the known PPARγ upstream regulatory mechanisms, we also speculate that the combination of G+E could affect either fatty acid–binding proteins or fatty acid transporters, which would potentially involve liver-gut crosstalk (61). In summary, we show that genetic and environmental factors synthesize to trigger unique biologic processes, resulting in a clinically relevant phenotype. Our data also provide complementary mechanistic insights into the role of Paneth cells in mediating CD pathogenesis (16, 62) and identification of actionable therapeutic targets. Methods Study design. The overall objective of our study was to determine the associations between the ATG16L1T300A genotype and exposure to cigarette smoking in triggering Paneth cell defects. For human subjects, based on the prevalence of adult CD subjects harboring type I Paneth cell phenotype (14, 15) and the natural history of CD after resection (1), 90 subjects were required to achieve a power of 80%. For in vivo experiments, we used a previously described mouse strain (Atg16l1T300A) that is known to possess Paneth cell defects (28). Cigarette smoking was performed following a previously described protocol (63, 64), with the cigarette filters removed. Paneth cell analysis was performed using immunofluorescence (14, 15) on distal ileum. All the experiments were performed in several replicates over the course of 2 years. At least 3 to 6 biological replicates were used for each group/experiment. The mice were randomized, and the investigator performing the histologic analysis was blinded to the sample identity. The design for microbiome studies included proper littermate controls and cohousing (65), and microbiome composition was analyzed using 16S rRNA-seq. Transcriptomic analysis was performed using RNA-seq. All data were included (no outliers were excluded). Additional details, including the total numbers per study group, are included in the respective figure legends. CD subjects. CD subjects who underwent ileocolectomy between 1999 and 2010 at Washington University or Cedars-Sinai Medical Center were previously described (14). A second CD cohort from Washington University composed of consecutive CD patients who underwent ileocolectomy between 2011 and 2013 were additionally included. Deidentified tissue samples from ileal resection margins that were free of acute inflammation were used for Paneth cell phenotype analysis. The following information was retrieved from the medical record: sex, age at operation, smoking history (never smoker vs. active/exsmoker), medication history (including immunomodulators and biologics), and endoscopic findings at the first visit 6 to 12 months after surgery. Recurrence was defined by endoscopy (Rutgeerts score ≥ i2). The genotypes of the patients were obtained using ImmunoChip (14) or through TaqMan genotyping assay (Thermo Fisher Scientific), with genomic DNA extracted from formalin-fixed, paraffin-embedded tissue based on the manufacturer’s instructions. Mice. Atg16l1T300A mice have been described before (28) and were a gift from Ramnik Xavier (Harvard Medical School, Boston, Massachusetts, USA). Heterozygotes were used to breed Atg16l1T300A and littermate controls. Atg16l1T300A mice were crossed with Tnfrsf1atm1/lmxmice (Tnfr1 KO; The Jackson Laboratory, 3244) to generate Atg16l1T300A Tnfr1–/– mice. PC-Cre mice were generated by introducing Cre recombinase gene driven by the α-defensin-4 promoter in the embryonic stem (ES) cells (44). The PC-Cre mice were subsequently crossed with Atg16l1fl/fl mice to generate PC-Cre+ mice. Mice with intestinal epithelium–specific knockout of Pparg were generated by crossing Ppargfl/fl mice (The Jackson Laboratory, catalog 004584) with Villin-Cre mice (The Jackson Laboratory, catalog 4586). All mice were on a C57BL/6 genetic background. The distal ileum of the mice (distal, 3 cm) was used for analysis in this study. Mouse treatments. Four- to six-week-old mice were exposed to cigarette smoking at 4 cigarettes per day for 5 days per week using Kentucky research cigarette 3R4F (with filters removed) (University of Kentucky, Lexington, Kentucky, USA) and a previously described protocol (64, 66). Mice were exposed to 2 weeks of smoking unless otherwise indicated and then sacrificed for tissue collection. For cohousing experiments, Atg16l1T300A and WT littermates designated as microbial recipients were exposed to an antibiotic cocktail of vancomycin, neomycin, ampicillin, and metronidazole for 2 weeks (36), followed by cohousing with mice of the same genotype that were exposed to cigarette smoking (microbial donors). Cohousing lasted 4 weeks, and the microbial donors continued to be exposed to cigarette smoking during this period. For the nicotine experiment, nicotine was added into the drinking water at a concentration of 0.1 mg/ml for 4 weeks. In other experiments to study effects of pharmacological agents in preventing cigarette smoking–induced Paneth cell defect, mice with the Atg16l1T300A genotype were exposed to smoking for 2 weeks. During this period, mice were administered either pan-caspase inhibitor Z-VAD-FMK (10 mg/kg/d) intraperitoneally (ApexBio) or Ultra-LEAF anti-mouse TNF-α antibody (0.5 mg/mouse/injection, 2 injections/wk) (BioLegend). For nec-1 inhibitor, mice received intraperitoneal administration of necrostatin (Sigma-Aldrich) at 4 mg/kg/d for 2 weeks. For rosiglitazone administration, mice received daily oral gavage with either PBS or rosiglitazone (Sigma-Aldrich) at a dose of 20 mg/kg/d for 2 weeks. Paneth cell phenotype analysis. Lysozyme and HD5 immunofluorescence was interpreted (by T.-C. Liu), as described previously (11, 14, 19, 20, 27). For both human and mouse samples, each Paneth cell was classified into normal or 1 of the 5 abnormal categories, including the following: disordered (abnormal distribution and size of the granules), diminished (≤10 granules), diffuse (smear of lysozyme or defensin within the cytoplasm with no recognizable granules), excluded (majority of the granules do not contain stainable material), and enlarged (rare, megagranules) (14, 27). The last 2 categories were only observed in human samples. The Paneth cell phenotypes of CD subjects (used for outcome correlation) were then defined by the percentage of total abnormal Paneth cells in the sample. The type I Paneth cell phenotype was defined as 20% or more of total Paneth cells showing abnormal morphology patterns, whereas the type II Paneth cell phenotype was defined as less than 20% of total Paneth cells showing morphologic defects (14). Statistics. Clinical outcome correlation was performed using log-rank test. For analysis between different genotype and smoking exposure combinations, Kruskal-Wallis tests followed by Dunn’s tests between groups were performed. For Paneth cell phenotype and various cellular readout comparisons in mouse experiments, 2-way ANOVA followed by Tukey’s multiple comparison adjustment was used. For microbiome studies, principle coordinate analysis was performed using analysis of similarities (ANOSIM) with 999 permutations. Relative operational taxonomic unit (OTU) abundance data were input into linear discriminant analysis effect size (LEfSe) to determine biomarkers with significant linear discriminant analysis effect size (67). The determination of sample size and data analysis for animal studies followed the general guideline of Festing and Altman (68). Based on the law of diminishing returns, Mead recommended that a degree of freedom (DF) of 10 to 20 associated with error term in an ANOVA would be adequate to estimate preliminary information (69). All tests were 2 tailed, and a P value of less than 0.05 was considered significant. Data were plotted and analyzed using GraphPad Prism (version 6.05) and SAS version 9.4 (SAS Institute). Data represent mean ± SEM. Study approval. The study was approved by the institutional review boards of Washington University School of Medicine and Cedars-Sinai Medical Center. Subjects provided written, informed consent. The animal studies were approved by the ethical committee at Washington University School of Medicine. Data and materials availability. All Atg16l1T300A mouse study full-thickness ileal RNA-seq data were deposited in the EMBL-EBI’s ArrayExpress database (E-MTAB-5707). All Atg16l1T300A mouse study LCM-procured Paneth cell microarray data were deposited in the ArrayExpress database (E-MTAB-6168). All 16s rRNA-seq data for Atg16l1T300A mice were deposited in the ArrayExpress database (E-MTAB-5717). All 16s rRNA-seq data for the cohousing experiment were deposited in the ArrayExpress database (E-MTAB-5720). Author contributions TCL, DPBM, and TSS designed the study. TCL, JTK, SX, GEK, and CBW acquired the data. DPBM recruited patients. MJH provided instruments for the experiments. MWR, RC, and GN provided mouse strains. TCL, KLV, FG, RDH, and TSS analyzed data. TCL and TSS drafted the manuscript. All the coauthors agreed on the content of the manuscript. Supplemental material Acknowledgments The study was supported by the Leona M. and Harry B. Helmsley Charitable Trust (to DPBM and TSS), Doris Duke Charitable Foundation grant 2014103 (to TCL), Crohn’s and Colitis Foundation grant 274415, NIH grants 1R56DK095820 (to DPBM and TSS), and P01 DK046763 and U01 DK062413 (to DPBM), K01DK109081 (to KLV), and UL1 TR000448 (to TCL). The authors thank the Genome Technology Access Center at Washington University School of Medicine for help with RNA-seq analysis. The Center is partially supported by National Cancer Institute grant P30 CA91842 and by Institute for Clinical and Translational Science/Clinical and Translational Sciences Award grant UL1 TR000448 from the NIH. The authors also thank Wandy Beatty in the Molecular Microbiology Imaging Facility for assistance with TEM and Robert Schmidt for interpretation of the TEM images. Footnotes Conflict of interest: The authors have declared that no conflict of interest exists. 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The inflammasome: a well‐regulated immune platform also present in non‐myeloid cells The canonical assembly of the inflammasome is a well‐regulated process that starts after the recognition of PAMPs or DAMPs by cytosolic receptors. The cytosolic receptor acts as a sensor protein and typically belongs to the NLR family but the activation of other receptors such as AIM2 also leads to the formation of an inflammasome5 (Table 1). The most studied inflammasome is NLRP3 because of its ability to respond not only to pathogens but also to sterile stimuli.7 Activation of the cytosolic receptor leads to the recruitment of the effector enzyme capase‐1. Depending on which cytosolic receptor is activated, the recruitment of the effector enzyme, caspase‐1, will require an adaptor molecule known as apoptosis‐associated speck‐like protein containing a caspase activation and recruitment domain (ASC) or not (Table 1). Upon oligomerization of the inflammasome, the effector enzyme caspase‐1 is activated and leads to the cleavage, maturation and release of IL‐1β and IL‐18, and to a form of cell death known as pyroptosis8 (Fig. 1). It is important to mention that, although most of the inflammasome‐forming receptors need ASC for their function, NLRP1b and NLRC4 have been shown to have both ASC‐dependent and ASC‐independent functions. Although ASC is dispensable (but significantly increases) NLRP1b function, NLRC4‐mediated pyroptosis (but not cytokine release) is ASC‐independent.9-11 Subfamily Receptor Requirement for ASC Main activating signal Main epithelia involved NLRP NLRP1 Yesa Anthrax toxin and ATP Oral, airway22-24 NLRP3 Yes Ionophores, crystals, ATP, bacterial toxins Oral, airway, intestinal, skin22, 23, 25, 26 NLRP6b Yes Microbiota‐modulated metabolites (taurine) Intestinal27 NLRP9b Yes Rotavirus dsRNA Intestinal28 NLRC NLRC4/IPAF Yesa Flagellin (in mouse)/Type III secretion system (in human) Intestinal29 Other inflammasome‐forming sensors AIM2 Yes dsDNA Oral, skin23, 30 Not all the inflammasome‐forming receptor proteins require the adaptor protein apoptosis‐associated speck‐like protein containing a caspase activation and recruitment domain (ASC) to activate caspases‐1, however, when present, ASC potentiates inflammasome activity. Also shown the main activating signals and epithelial distribution. a Both nucleotide NACHT, LRR and PYD domains‐containing protein 1 (NLRP1) and NLRC4 protein have a caspase recruitment domain and have shown activity in the presence or absence of ASC.9, 31 b The ability of NLRP6 to form inflammasomes has only been suggested but not directly shown. Although canonical inflammasomes rely on the activation of caspase‐1, cells can also form ‘non‐canonical’ inflammasomes, which lead to the activation of caspase‐11 (caspase‐4 and caspase‐5 in humans) or caspase‐8.13, 14 Caspase‐11 acts as an intracellular lipopolysaccharide (LPS) sensor by direct binding using its caspase activation and recruitment domain (CARD). Interestingly, this process is widely extended into myeloid and non‐myeloid cells.15 Therefore, caspase‐11 could be a widespread mechanism to detect intracellular Gram‐negative bacteria in cells, including infected epithelial cells. Upon LPS recognition, caspase‐11 is activated and causes K+ efflux, which induces NLRP3 canonical inflammasome formation and IL‐1β and IL‐18 release.16 Both IL‐1β and IL‐18 are potent pro‐inflammatory cytokines with a pivotal role during the first steps of inflammation and their deregulation is extremely detrimental to health. Hence, these are tightly regulated proteins, not only at transcriptional level, but also post‐transcriptionally by their activation within the inflammasome. Although IL‐1β and IL‐18 are activated by the inflammasome in a similar manner, their contribution to the inflammatory response is very different. Interleukin‐1β drives inflammation by controlling the recruitment of neutrophils to the site of infection, the induction of IL‐8 by epithelial cells and the release of IL‐17 from T cells.17 On the other hand, the main role of IL‐18 is to foster the activation of natural killer and T cells and the release of interferon‐γ.18-20 Although most studies focus on the release of IL‐1β and IL‐18 by immune cells such as macrophages, epithelial cells are also able to release these pro‐inflammatory cytokines.19, 21 However, the mechanistic insights by which this occurs remain unclear. As a result of their essential role as triggers of innate immunity, and in order to tightly control their release, IL‐1β and IL‐18 are synthesized as pro‐forms lacking a signal peptide. The maturation and release of these pro‐inflammatory cytokines are regulated by the assembly of a multiprotein complex known as the inflammasome, also present in epithelial cells (Table 1; Fig. 2).22 Despite caspase‐1 being the main caspase involved in this process, others such as caspase‐4/5 (human orthologues of murine caspase‐11) and caspase‐8 can also play an important role.13, 32 Recently, a new protein‐mediating pyroptosis has been described: gasdermin‐D.33, 34 Gasdermin‐D is activated by caspase‐1 and forms pores in the membrane, which leads to cell death.35-38 It has been recently proposed that IL‐1β and IL‐18 release happens through gasdermin‐D pores;39 even so, further research is needed. Gasdermin‐D is also expressed in epithelial cells, and its involvement on inflammasome activity has been reported. Although no direct cleavage of gasdermin‐D has been shown in epithelial cells, the pore‐forming protein has been shown to be necessary for NLRC4‐mediated and NLRP9b‐mediated pyroptosis.28, 40, 41 This would show that gasdermin‐D is functional and important for epithelial cell inflammasome function. Interestingly, in recent years, it has been reported that under certain circumstances the release of pro‐inflammatory cytokines and cell death are uncoupled upon inflammasome activation in several cell types such as neutrophils, monocytes and macrophages.39, 42, 43 This is particularly important for epithelial cells where the conservation of the integrity of the epithelial layer is key to maintain barrier homeostasis44 (Fig. 2). Whether the release of IL‐1β and IL‐18 is uncoupled from cell death in epithelial cells remains unknown. Despite increasing research in this area, there are still unanswered questions regarding inflammasome activation in the epithelium (Fig. 2). The epithelium is exposed to mechanical and chemical damage associated with the exterior milieu as well as to a wide range of microorganisms colonizing our body. Hence, the inflammasome activity has to be tightly regulated in epithelial cells, not only to prevent an inflammasome response to healthy microbiota but also to potentiate the response to an altered microbiome. In this review, we will summarize the current knowledge on inflammasome activation at different barrier sites, and how these molecular complexes contribute not only to maintenance of barrier homeostasis but also to disease. Gut epithelial cells The most studied inflammasome‐forming epithelium is the gut epithelium. In this barrier, the heavy colonization of commensal microbiota makes the tight regulation of the inflammatory cascade crucial. How gut epithelial cells respond to invasive pathogens and not to commensal bacteria remains only partially understood. It has been shown that differential distribution of TLRs on the membrane of gut epithelial cells allows the response to invasive microorganisms not just after apical contact but after the disruption of the epithelium47 (Fig. 2). The requirement of invasion or damage of epithelium integrity to activate the immune function of epithelial cells guarantees that repair mechanisms and inflammatory processes are triggered only when needed. In addition to TLRs, the cytosolic localization of the inflammasome‐forming sensors NLRs and AIM2, and their ability to respond to damage signals as well as to pathogens, places them as ideal platforms to detect pathogen invasion. The role of inflammasomes at this barrier became apparent after early reports showed that intestinal epithelial cells (IEC) were able to up‐regulate IL‐1β in response to infection48 as well as being the principal contributors to the total levels of IL‐18 in the gut under physiological conditions.49 Since then, an increasing amount of evidence has shown an involvement of the inflammasome in maintaining homeostasis in this barrier as well as responding to pathogens. The gut epithelium has been shown to rely on the NLRC4 inflammasome to respond to Citrobacter rodentium, a mouse model of enteropathogenic Escherichia coli infection.29, 50 Interestingly, epithelial NLRP3 is also involved in C. rodentium clearance as Nlrp3−/− mice show higher bacterial burden and higher epithelium invasion.51 This effect is likely to be mediated by both IL‐18 and IL‐1β as Il‐18−/− and Il‐1β−/− mice present a similar phenotype to the Nlrp3−/− mouse when challenged with C. rodentium.50 These findings have also been confirmed in human cells after E. coli infection of the epithelial cell line Caco‐2 induced increased levels of IL‐18 release.52 Apart from this role in infection, caspase‐1 and NLRC4 have also been reported as essential in preventing colonic inflammation‐induced tumorigenesis by regulating the response of epithelial cells to injury, highlighting the role of NLRC4 in epithelial cells.53, 54 In another model of infection, inflammasome‐dependent release of IL‐18 has been shown to mediate natural killer cell recruitment after Salmonella typhimurium infection.55 Although authors do not investigate the origin of gut IL‐18 in this paper, the above‐mentioned studies suggest that this IL‐18 is likely to be of epithelial cell origin. Using the same infection model, it has been shown that inflammasome‐forming sensors are also involved in the extrusion and expulsion of intestinal epithelial cells. During S. typhimurium infection, caspase‐4 mediates epithelial cell expulsion through a process dependent on pyroptosis.56 This process is epithelial cell intrinsic and independent of cytokine signalling, showing a specific role for pyroptosis and for non‐canonical inflammasomes.57 However, this is not the only inflammasome‐dependent mechanisms for epithelial cell expulsion. In another study exploring the role of NLRC4 in gut epithelial cells, authors showed that caspase‐1 and gasdermin‐D are dispensable for IEC expulsion from the epithelial layer upon treatment with the NLRC4 activator FlaTox (Legionella pneumophila flagellin fused to Bacillus anthracis lethal factor), as cells were still expelled from the epithelium in the absence of these mediators. In contrast, the expelled cells were not dead, implying that both caspase‐1 and gasdermin‐D are required for IEC pyroptosis upon NLRC4 activation.41 How the two mechanisms can act together is still not understood. Although this is an important mechanism necessary for the maintenance of normal microbiota and pathogen clearance, all these studies highlight the danger of excessive inflammasome response and gasdermin‐D‐mediated pyroptosis in gut epithelial cells. An excessive activation of pyroptosis could eventually lead to loss of membrane integrity and systemic infection. Another NLR involved in the relationship between gut epithelium and bacteria is NLRP6. Recent findings emphasize the importance of having proper controls to elucidate the role of different inflammasomes in immunity, especially in maintaining commensal bacteria. Although the role of NLRP6 in gut epithelial cells is still not totally clear, NLRP6 is highly expressed and functional in gut epithelial cells.27 Mamantopoulos et al.,58 in two different animal facilities, dismissed a role of NLRP6 in maintaining homeostasis in the gut microbiota at steady state. However, it has been proposed that NLRP6 does contribute to microbiota balance, but this contribution is dependent on microbiota community structure (and especially in the presence of pathobionts such as Helicobacter spp.). Both of these studies point to familial transmission of microbiota rather than NLRP6 impairment for the observed changes in previous studies.59, 60 How the cells activate NLRP6 and whether NLRP6 forms an active inflammasome are still not fully answered questions. No direct evidence shows NLRP6 forming an inflammasome but Nlrp6−/− studies mimic the results of Caspase‐1−/− and Asc−/−, suggesting that this might be the case.61, 62 Recently, taurine, an amino acid present in bile acid and shown to regulate gut microbiota, has been proposed to be the activating signal for NLRP6 as it induces IL‐18 secretion in wild‐type mice but not in Nlrp6−/− mice.62, 63 Although this finding needs to be further tested and investigated, it would be highly interesting as the gut microbiota in return has also been shown to regulate bile acid metabolism and especially taurine.64 Further research is needed to elucidate the molecular events leading to NLRP6 activation. A highly prevalent condition of the gut is inflammatory bowel disease (IBD, including Crohn's disease and ulcerative colitis). IBD is a chronic inflammation of the digestive system associated with the alterations of the gut microbiota.65 The most common mouse model of IBD is to induce colitis using dextran sodium sulphate (DSS), which damages the epithelium, increasing gut permeability.66 Inflammasome responses in experimental models of colitis are well characterized, but mainly in monocytes and macrophages.67 In such models, NLRP3 inhibition ameliorates DSS‐induced colitis.68-70 However, these studies fail to show a specific role for epithelial cells, despite these being the main cell type affected by IBD. In fact, recent studies suggest that NLRP3 is not expressed by epithelial cells in the colon of mice, placing tissue‐resident macrophages as the principal contributors to this NLRP3‐dependent response.71 These studies suggest that although NLRP3 is a main actor in IBD, the epithelial cell layer's contribution to IBD might be NLRP3 independent. Surprisingly, epithelial cell‐specific depletion of capase‐1 induces decreased IL‐18 levels and decreased pathology in a DSS‐induced colitis model, pointing to the involvement of another inflammasome‐forming receptor.72 This is consistent with the finding that during colitis, IL‐18 produced by epithelial cells exacerbates pathology. Interestingly, epithelial IL‐18 signalling during colitis targets epithelial cells themselves as Il‐18R−/− in haematopoietic cells fails to rescue mice from colitis, whereas specific Il‐18R−/− in epithelial cells protects mice from DSS‐induced colitis.73 Recent studies also point to a role of AIM2 in DSS‐induced colitis. AIM2 knockout mice are more severely affected by colitis and present a higher bacterial burden; however, how AIM2 is activated or how DNA is delivered in the epithelial cells during colitis is unknown. In fact, authors suggest that the role of AIM2 in colitis is to control the anti‐microbial peptide production (such as α‐ and β‐defensins) in IEC, and to regulate tissue repair, activating an IL‐18‐dependent pathway.74, 75 All these reports together show an increasingly recognized role of inflammasomes in innate immunity driven by gut epithelial cells and places the inflammasome response as a coordinated process with several outcomes. However, a more profound study using IEC or myeloid‐cell‐specific knockout mice would be useful to better understand the role of epithelial cells in barrier defence. Lung epithelium Due to the extended area of contact between internal and external stimuli, airway epithelium is a primary target for pathogens and damaging agents. Lung epithelial cells have been shown to activate the inflammasome and release IL‐1β and IL‐18 upon a diverse range of stimuli such as influenza virus, ozone, particulate matter, or asbestos.76-79 However, despite the importance of the release of IL‐1β and IL‐18 in this organ, the events leading to their release from epithelial cells are still not well understood and are the subject of controversy, probably partly due to different cell types used in different studies. For instance, the involvement of caspase‐1 is not clear because some studies show that epithelial cell lines (Beas2Bs, 16HBE, Calu‐3) and also primary cells (human bronchial epithelial cells) express little to no caspase‐1 in an infection model, whereas others show a role for caspase‐1 in epithelial cells (for instance in Beas2Bs, mouse tracheobronchial epithelial cells and A549).80-83 It has been suggested that as some of these cells do not express the inflammasome component, caspase‐11 is responsible for the inflammasome response to infections, probably by direct biding of LPS.84 These differential results highlight the importance of analysing the expression of inflammasome components in the lung epithelial cell lines before conducting inflammasome experiments and the need to work in mouse and human primary cells. As in the gut, the lungs constitute an area that is heavily colonized by commensal bacteria. However, in contrast to the gut, the lung epithelium is also heavily exposed to agents causing sterile inflammation such as particulate matter present in tobacco smoke or urban pollution. Despite the fact that airway macrophages respond strongly to particulate matter due to their increased ability to phagocytose, epithelial cells also respond to air pollutants.85 Human bronchial epithelial cells (Beas2B) have been shown to up‐regulate, process and release IL‐1β in response to crystal silica exposure, which is found in the air and taken up by epithelial cells.83 Interestingly, in the same study, they also detect release of High mobility group box 1 protein (HMGB1) from epithelial cells after silica exposure. HMGB1 is a potent danger signal also released by A549 cells under infection.82 These observations are relevant because the crosstalk among epithelial cells and between epithelial cells and immune cells is important for tissue repair. Other urban particulate matter (particulate matter < 10 µm) can also activate the inflammasome in an NLRP3‐dependent manner.79 This could be particularly important in urban or industrial areas. This particulate matter uptake by epithelial cells and inflammasome activation could worsen already existing conditions or cause new ones. In fact, it has been suggested that following periods of poor air quality (characterized by higher levels of particulate matter), inflammasome activity could be contributing to the exaggerated response to viruses such as influenza and allergy.21, 86 Another major agent for lung dysfunction, cigarette smoke, increases the release of IL‐1β in human lung epithelial cells, and this increase is even higher in patients with chronic obstructive pulmonary disease (COPD).87 Indeed, IL‐1β has been shown to be a marker of COPD severity as individuals with COPD present higher levels of IL‐1β in serum.88 In contrast, another study shows that cigarette smoke reduces the inflammatory response in mice treated with another NLRP3‐activating crystal: asbestos.89 Although contradictory, the reduction of the inflammatory response could be explained by the promotion of the proteasomal degradation of NLRP3 mediated by its ubiquitination.90 In addition to sterile agents, the lung is also exposed to pathogens. A condition where the lung epithelium integrity is compromised is during aspergillosis. Being inhaled every day, the spores of Aspergillus fumigatus invade the lung of not only immunocompromised patients but also patients with COPD.91 Inflammasomes have long been involved with the innate immune response to A. fumigatus, and recent studies show that inflammasome activation occurs early during infection and is key for macrophage anti‐fungal activity.92, 93 Interestingly, β‐glucan, a component of the A. fumigatus cell wall, upon dectin‐1‐binding activates NLRP3 inflammasome in bronchoepithelial cells.94 In fact, Syk tyrosine kinase, a kinase activated through dectin‐1, has been shown to be involved in inflammasome activation by A. fumigatus in monocytes, reinforcing the role of β‐glucan in inflammasome activation in lung epithelial cells.95 Both studies point at reactive oxygen species, a major mediator of inflammasome activation, as a key factor during aspergillosis. The complexity of the lung together with the distinct environments and stimuli that lung epithelial cells face makes the study of the epithelial inflammasome in this organ quite challenging. However, these studies show the inflammasome in the lung as a clear therapeutic target to ameliorate a broad range of pathologies with an inflammatory component. Oral epithelium An entry gate for nutrients, the oral mucosa is a heavily exposed environment where particulate matter, and bacterial and fungal agents constantly challenge the homeostasis of the epithelium. Gingivitis is inflammation of the gums, where the gum pulls away from the bone, creating cavities that are colonized by pathogens, which if left untreated can lead to periodontitis. One of the main pathogens colonizing these cavities and causing the disease is Porphyromonas gingivalis. Periodontitis has been linked to increased expression of inflammasome‐sensing proteins NLRP3 and AIM2, mainly in the epithelial layer.22, 96 Moreover, a polymorphism in other NLR family member, NLRC5, has been linked to increased susceptibility to periodontitis,97 although how it contributes to this pathology has not been investigated. NLRC5 has a caspase recruitment domain but it has not been shown to form inflammasomes on its own. In fact, NLRC5 can associate with NLRP3 in response to different PAMPs and DAMPs to cooperatively activate the inflammasome.98 This would suggest that the polymorphisms of NLRC5 induced to increased susceptibility to periodontitis are the consequence of an aberrant assistance to NLRP3 to form inflammasomes. Other roles for NLRC5 have been described including negative regulation of nuclear factor‐κB,99 interferon signalling99, 100 and regulation of major histocompatibility complex class I genes,101 all of which could also explain its contribution to periodontitis. As expected, infection of gingival epithelial cells with P. gingivalis induced an increase in Il‐1β gene expression. However, IL‐1β was left unprocessed and accumulated intracellularly. Interleukin‐1β was only processed and released after the activation of the ATP‐gated receptor P2X7, which led to NLRP3 inflammasome formation. The P2X7R is also involved in NLRP3 inflammasome formation and release of mature IL‐1β from salivary epithelial cells, as the release of this pro‐inflammatory cytokine is dampened in P2X7R knockout mice.102, 103 Why IL‐1β remains uncleaved and is intracellular during P. gingivalis infection remains an interesting question. We could speculate that the immune machinery of epithelial cells might reduce the activation of caspase‐1 during chronic infection. This mechanism could potentially dampen immune reactions to commensal bacteria and prevent pyroptosis to maintain the integrity of the epithelial layer. In fact, in macrophages, it has been shown that IL‐1β can be released via exosomes in a mechanism dependent on NLRP3 and ASC but independent of caspase‐1.104, 105 Potentially, IL‐1β produced by epithelial cells could be stored and released on exosomes to have two potential effects. (i) Be processed by other cells (potentially immune cells) to avoid activating caspase‐1 and compromising the epithelial layer in epithelial cells. (ii) Have an effect in areas distant to the site of infection. Although epithelial cells have been shown to release cytokines trapped in exosomes, it is unknown whether IL‐1β could follow the same pathway.106 Interestingly, another NLR family member, NLRX1, has recently been shown to potentiate the inflammasome response to ATP in gingival epithelial cells through the generation of mitochondrial reactive oxygen species. However, how NLRX1 (not predicted to form inflammasomes) potentiates the response to ATP is not well understood and might assist NLRP3 in its function in a similar manner to NLRC5.107 Although inflammasome activity is required for optimal control and clearance of pathogens, over‐activation could lead to unwanted outcomes. Excessive levels of IL‐1β and of pyroptosis have been linked to bone loss during periodontitis and to malignancy during oral carcinogenesis.108, 109 Epithelial cells can avoid this and reduce the extent of inflammasome activity during acute infection through the stress‐induced enzyme haem oxygenase‐1. This enzyme has anti‐oxidant and anti‐inflammatory effects, and can dampen LPS signalling and inflammasome activity in oral epithelial cells, although the exact mechanism by which this occurs is not clear.110 Skin epithelial cells The skin is the main physical barrier that protects our body from the external environment, therefore it is active in the immune control of pathogen invasion. Immune homeostasis in the skin is essential to maintain skin integrity and its role as a barrier. Although the role of the inflammasome in skin is not well characterized, mutations in different genes coding for NLR‐forming inflammasomes have been associated with skin conditions. Even before the discovery of the inflammasome, mutations in the NLRP3 gene were found to cause a spectrum of diseases known as cryopyrin‐associated periodic syndromes (or CAPS), which are associated with skin inflammation and rashes.111 Rashes typically disappear, or are controlled, after anti‐IL‐1β therapy, showing a role for IL‐1β signalling in skin rashes and in CAPS in general.112 Recently the first genetic evidence connecting inflammasome signalling to non‐fever skin diseases has been found. Gain of function mutations in the NLRP1 sensor protein cause two overlapping skin disorders: multiple self‐healing palmoplantar carcinoma and familial keratosis lichenoides chronica. These mutations lead to spontaneous inflammasome activation and paracrine IL‐1 signalling in keratinocytes from these patients.24 Polymorphisms of NLRP1 have also been associated with the autoimmune disease vitiligo, a condition characterized by the development of white patches in the skin due to lack of melanin.113 This is believed to occur through higher IL‐1β production and NLRP1 activation, although the specific mechanism by which the NLRP1 inflammasome shows greater functional activity is not known.114 Inflammasome has also been involved in another chronic inflammatory syndrome affecting the skin. Deregulated levels of IL‐1β and AIM2 inflammasome activity by keratinocytes have been linked to psoriatic disease. Abnormally high levels of IL‐1β could potentiate a T helper type 17 response with up‐regulation of IL‐17 and excessive infiltration of neutrophils, characteristics of psoriatic diseases.115 It is not surprising that AIM2, a receptor involved in the recognition of cytosolic DNA, is involved in psoriatic diseases as cytosolic DNA has been shown to be responsible for inflammasome activation in keratinocytes during psoriasis.116 Interestingly, a recent study points to a role in AIM2 in immune memory of epithelial cells.30 Using epithelial cell stem cells they determined that these cells possess immune memory, enabling a rapid second response after a previous exposure to inflammation. This striking capacity of skin epithelial stem cells is dependent on AIM2 and downstream of IL‐1β as Il‐1β−/− and Il‐1r1−/− but not Il‐18−/− failed to induce immune memory. Given the above‐mentioned role of AIM2 in recurrent skin diseases such as psoriasis, we could speculate that both mechanisms might be linked, suggesting major implications for immune memory of epithelial cells in chronic inflammatory diseases. Finally, the role of IL‐18 in skin has been widely studied. In fact, IL‐18 has been linked with psoriatic disease, where increased caspase‐1 activity has been reported.117 Variations in the IL‐18 gene have also been associated with increased risk of atopic eczema, a chronic inflammatory condition of the skin.118 Final remarks In this review we have presented the involvement of inflammasome activation in the role of epithelial cells as mediators of the immune response. We have reviewed how epithelial cells are able to release IL‐1β and IL‐18. However, despite the relatively low concentration of these cytokines released by epithelial cells compared with macrophages, it is important to mention that in healthy conditions epithelial cells are relatively more abundant in barriers than immune cells. Therefore, the epithelial compartment could contribute greatly to the inflammatory response to pathogens, at least in early infection when not many immune cells have been recruited. We have highlighted the diversity of responses and of sensor proteins involved in the inflammasome response. The differential expression of sensor molecules and inflammasome components and mediators in the different types of epithelial cells will shape the immune response according to the needs and threats of each specific site. Similarly, the types of pathogens and threats that each barrier will face vary from one epithelium to another, raising the question of whether there is a general mechanism leading to inflammasome activation in epithelial cells or the response is specific to each epithelium and threat. The increasing body of publications in the field points in the direction of several types of inflammasomes involved in different epithelia, making the response tissue‐dependent. We conclude that, in order to better understand this question, the field would benefit from a broad study comparing the involvement of different inflammasomes in the different epithelia. Even more, it is not always clear and differs from one cell line model to another what inflammasome components are present in each epithelium. In our review we have highlighted several examples of differential expression of inflammasome components or pro‐inflammatory cytokines in different cell types or tissues. We could hypothesize that within one organ, different types of epithelial cells will express different inflammasome components, including cytosolic sensors and effector caspases. That would ensure a diverse, adapted and targeted response and prevent a much feared loss of epithelial integrity by massive activation of inflammasomes. It is also important to highlight that most of the available data on the role of inflammasomes in epithelial cell immunity has been obtained using either human cell lines, or primary epithelial cells from mouse. Key differences between human and murine inflammasomes have already been described (for instance NLRC4 is not activated by the same components of bacterial flagellum in mouse and humans and DNA inflammasome activation in human monocytes depends on NLRP3 instead of AIM2119, 120). Therefore, more studies are needed in human lung epithelial cells to confirm the findings mentioned in this review. Gasdermin‐D, as mentioned before, is the executor of pyroptosis. However, its role and function in non‐haematopoietic cells is still not well characterized. We could speculate that after inflammasome activation in epithelial cells, the triggering of pyroptosis could have two possible outcomes, both of them highlighting the need for a tight control of pyroptosis in epithelial cells. Pyroptosis during infection could be detrimental (and would be somehow silenced or dampened in epithelial cells) by causing membrane integrity loss. This result is in line with the previously mentioned report showing accumulation of pro‐IL‐1β during P. gingivalis infection of the oral mucosa. Nevertheless, pyroptosis could also be beneficial during epithelium colonization, as could a mechanism of containing the infection and avoiding further invasion of internal layers of the epithelium. To reinforce this idea, during Salmonella infection caspase‐1 and gasdermin‐D cleavage are required for IEC pyroptosis but not for IEC expulsion.41 In fact, in that study, the authors demonstrate that during the death and expulsion of IEC, the epithelial integrity is maintained through the rearrangement of neighbouring cells. This result also links with the discovery that small amounts of caspases‐1 are required for gasdermin‐D cleavage (meaning that even a weak activation of inflammasome produces cell death) while detecting active IL‐1β requires higher levels of processed caspases‐1.121 In such a scenario, weak invasion of the epithelial layer would lead to epithelial cell death and expulsion but still no immune response as the threshold to release IL‐1β is much higher than for cell death. This mechanism, potentially occurring with low infection rates where few cells are being infected, could be important to maintain the equilibrium with normal microbiota. The recent discovery of inflammasome inhibitors such as MCC950 or boron‐based compounds is opening the path to the future treatment of inflammasome‐related pathologies with specific drugs.122, 123 However, while the field is moving towards better drugs, there is also an increasing body of evidence that inflammasome activity is key in the immune response of many cell types. The potential specific targeting of either immune cells or epithelial cells in different inflammasome‐related pathologies would be beneficial. Such a specificity would allow the targeting of the over‐activation of inflammasome in cells where its activity is detrimental while allowing the normal inflammasome function in other cells. In conclusion, the role of the inflammasomes in epithelium has been extensively reported. We hypothesize that their contribution to the triggering of inflammation, in opposition to the common belief, is far from being negligible. This combination of findings provides some support for the conceptual premise that targeting inflammasome activity in epithelial cells might be essential for further treatment of a wide range of inflammatory disorders. There is then, abundant room for further progress in elucidating the mechanism of inflammasome activation in epithelial cells and investigating whether it is similar to that in macrophages or not.
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Citation: Sullender ME, Baldridge MT (2018) Norovirus interactions with the commensal microbiota. PLoS Pathog 14(9): e1007183. https://doi.org/10.1371/journal.ppat.1007183 Editor: Richard C. Condit, University of Florida, UNITED STATES Published: September 6, 2018 Copyright: © 2018 Sullender, Baldridge. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: MTB was supported by NIH grant K22 AI127846-01, DDRCC grant P30 DK052574, and the Global Probiotics Council’s Young Investigator Grant for Probiotics Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Introduction Human norovirus (HNoV) is the leading cause of epidemic nonbacterial gastroenteritis worldwide, causing an acute diarrheal infection and occasionally chronic infection in immunocompromised individuals. Mouse and tissue culture models utilizing murine norovirus (MNoV) have allowed for interrogation of viral mechanisms of infection and pathogenesis. Here, we outline the interactions between the commensal microbiota of the intestine and norovirus and their implications (Fig 1). Download: PPT PowerPoint slide PNG larger image TIFF original image Fig 1. Norovirus pathogenesis is affected by many factors in the enteric environment. a) The presence of commensal bacteria allows for efficient MNoV infection, with tuft cells being one rare cell population infected. b) Absence of commensal bacteria reduces MNoV titers by depleting tuft cell populations and potentially altering innate immune responses during persistent MNoV infection. c) Binding of HNoV to HBGA-positive enteric bacteria has been found to facilitate infection of B cells. d) Sialic acid moieties on the cell surface have been found to act as coreceptors for MNoV infection of macrophages, while bile acids have been found to be important for the establishment of HNoV infection of enterocytes. e) MNoV infection has been found to trigger the expression of IFN-λ in infected cells, up-regulating interferon simulated genes that restrict viral replication and subsequent spread of infection—the mechanism of this process has yet to be characterized, but commensals are believed to play a major regulatory role. HBGA, histo-blood group antigen; HNoV, human norovirus; IFN-λ, interferon lambda; MNoV, murine norovirus. https://doi.org/10.1371/journal.ppat.1007183.g001 Question 1: Is norovirus infection in mice a good model for norovirus infection in humans? Due to the fact that HNoV cannot readily grow in mice and, until recently, has not been culturable in vitro, the use of MNoV has provided robust animal and tissue culture model systems, which allow for mechanistic studies of an orthologous pathogen [1–4]. The MNoV model system allows for the merging of basic mechanistic principles of infection and replication from cell culture systems to pathogenesis in a host system that is both genetically malleable and affordable. Thus far, MNoV studies have allowed for the elucidation of a species-specific proteinaceous receptor (CD300LF) and viral tropism for a rare intestinal epithelial cell population called tuft cells during persistent infection as well as macrophages, dendritic cells, and lymphocytes during acute infection in vivo [5–7]. Many external factors outside of the narrow window of host cell–virus interactions that affect NoV pathogenicity have also been identified, such as bile, sialic acid, and intestinal bacteria [2,5,6,8]. Additionally, host mucosal cytokine interferon lambda (IFN-λ) has recently been identified as a potent anti-NoV molecule, opening the possibility of its therapeutic use for HNoV in the future [9]. Multiple strains of MNoV allow for the study of both chronic (MNV.CR6, MNV-3) and acute (MNV-1, MNV-1.CW3) infection, further adding to the strengths and complexity of this model system [10]. Despite some differences in symptom presentation and species-specific receptors, HNoV and MNoV exhibit many similarities in cellular tropism, requirement of carbohydrate attachment factors, and potential for persistent viral shedding after symptom resolution [3,10]. However, some clinical symptoms do differ between MNoV and HNoV infections, most notably the lack of vomiting and inability to produce more than statistically significant mild diarrhea in mice [11]. Question 2: Do all strains of norovirus depend on the commensal microbiota for infection? A large and diverse population of commensal microbes, consisting of bacteria, viruses, fungi, and parasites, reside within the intestinal lumen. NoV, being an enteric pathogen, encounters and interacts with members of this community, resulting in outcomes beneficial or detrimental to the host. HNoV has been found to interact directly with commensal (Enterobacter cloacae) and pathogenic (Clostridium difficile) bacterial species via the viral capsid and histo-blood group antigen (HGBA)-like carbohydrates expressed on bacterial surface membranes [12,13]. In addition, both HNoV and MNoV have been reported to bind sialic acid residues, which can be expressed on bacteria, suggesting that MNoV could also interact directly with the enteric microbiota [4,14]. Experimental alteration of the enteric microbiota with oral antibiotics drastically depletes the intestinal bacterial population. This in turn reduces the severity of acute MNoV infection (reduced MNV-1 titers) and also prevents or reduces persistent infections (drastically reduced MNV.CR6 and MNV-3 titers) in the ileum and colon [15]. Additionally, infection by MNV.CR6 can be rescued by fecal microbiota transplant (FMT) from nonantibiotic-treated to antibiotic-treated mice, highlighting the importance of commensal bacteria for MNoV infection [15]. While all murine NoV strains tested and reported thus far exhibit a dependence upon commensal bacteria for infection, further studies will be needed to determine whether this is a phenomenon affecting all HNoV and MNoV strains and to define strain-specific mechanisms. One putative explanation by which bacteria can promote MNoV infection comes from the recent description of tuft cells as the physiologic target cell of persistent MNoV infection and propagation. Within the mouse intestine, tuft cells are regulated by commensal bacteria such that antibiotic treatment correlates with reduced numbers of tuft cells and leads to reduced viral titers [6]. In addition to commensal bacteria, parasitic worms (such as Trichinella spiralis) also exhibit a proviral effect in the context of MNoV infection [16,17] via induction of tuft cells by type 2 immune responses (IL-4, IL-25 cytokines) [6]. Thus, both bacteria and enteric metazoans can regulate NoV infection. In addition to microbe–NoV and microbe–host interactions impacting viral pathogenesis, NoV infection itself can also alter the enteric microbial communities of the host. This virus-induced dysbiosis is characterized by an enhanced Firmicutes to Bacteroidetes ratio. This alteration is seen both in a subset of HNoV infections and early acute MNoV infections (MNV-1) [18,19]. However, this effect was not detected in longitudinal studies of both acute and persistent strains of MNoV (MNV-1, MNV.CR6, and MNV-4), suggesting potential temporal or facility-based effects [20]. Question 3: How do commensal bacteria regulate enteric virus infections via immune skewing? The host intestinal immune system is highly regulated by a complex interplay of various lymphoid tissues, immune cells, cytokines, and their receptors [21–23] and possesses three distinct layers: mucus, epithelia, and lamina propria. In the small intestine, mucus-secreting goblet cells and antimicrobial peptide-secreting Paneth cells form the mucosal barrier that segregates commensal bacteria from the intestinal epithelia [24]. Intestinal epithelial cells directly interact with and survey the gut environment in coordination with innate lymphoid cells, which communicate with the immune system via secretion of cytokines and chemokines [24–26]. Dendritic cells ferry antigen from the lumen across the epithelial barrier to draining lymph nodes and mucosal lymphoid tissues in the lamina propria [27], and innate inflammatory signals and other luminal signals activate T- and B-cell responses [26]. These interacting layers play a large role in maintaining the microbiota and host immune system in homeostasis as well as regulating infection, inflammation, and autoimmunity. While the interactions between commensal bacteria, enteric viruses, and the intestinal immune system are still poorly understood, several recent studies have suggested important interplay between these factors. Innate immune responses are primed via commensal bacterial recognition by the enteric epithelium, which activates antiviral intestinal responses after a secondary viral-induced signal within the gut [22]. In contrast, mouse mammary tumor virus (MMTV) has evolved to evade innate immune responses by binding bacterial lipopolysaccharide, inducing the immunosuppressive cytokine IL-10 via Toll-like receptor signaling pathways [21]. This effect is entirely dependent upon the microbiota; mice receiving parenteral administration of MMTV do not experience a suppressed immune response, and antibiotic-treated or germ-free mice receiving MMTV orally fail to pass MMTV to their offspring. Microbial modulation of innate immunity also offers a second explanation of the preventive effect of antibiotics on MNoV infection: it is the result of the bacterial microbiota hindering a yet-to-be-identified immune pathway, which limits the antiviral efficacy of IFN-λ during persistent MNoV infection [23]. Evidence for this comes from experiments demonstrating that mice lacking IFN-λ signaling no longer require commensal bacteria for successful MNoV infection [23]. This triangle of interactions—commensals, viral pathogen, and host—produce anti- or proviral environments through many disparate and yet-to-be-characterized mechanisms. Question 4: Does a dependence on the commensal microbiota apply to other viruses? Other enteric viruses, including rotavirus and poliovirus, have been found to depend on enteric bacteria to infect, similar to MNoV [28,29]. Commensal bacteria act as a proviral factor during poliovirus infection, as antibiotic treatment results in mice being less susceptible to infection and a reduced viral load in the intestine [28]. The mechanism underlying this involves viral particles binding to bacterial lipopolysaccharide, causing enhanced host cell receptor binding and virion stability [28,30]. Paradoxically, microbial depletion was found to increase antibody responses against rotavirus, which may contribute to enhanced viral clearance during antibiotic treatment [29]. In contrast, nonenteric viral infections are enhanced in mice depleted of commensal bacteria. For neurotropic flavivirus (West Nile, dengue, Zika) infections, depletion of the enteric microbiota significantly increased viral susceptibility, viral burden, disease severity, and lethal outcomes in mice [31]. Additionally, respiratory influenza A virus (IAV) and lymphocytic choriomeningitis virus (LCMV) infection have been found to be intensified (sustained, high viral titers in lung tissue and serum, respectively) due to impaired immune responses secondary to depletion of gram-positive bacteria in the gut [32,33]. In these cases, antibiotic treatment reduced virus-specific cluster of differentiation 8+ (CD8+) T-cell responses, though there is apparent variation in the manifestation of defects. Antibiotic treatment resulted in decreased numbers of dendritic cells (DCs) for antigen presentation in the case of flavivirus infection, whereas in the case of IAV and LCMV, there was a defect in DC migration to lymph nodes attributed to reduced inflammasome activation upon infection [31,32]. The bacterial metabolite desminotyrosine was also found to regulate type I IFN signaling in the lung to control IAV infection [32,34]. These findings suggest that bacteria interact with both innate and adaptive immune systems to control both local and systemic antiviral responses, leading to distinct outcomes for enteric and nonenteric viruses. Question 5: Does microbiome modulation have therapeutic potential for infectious diseases in humans? While it is clear that the microbiome plays a significant role in both infectious and noninfectious diseases alike, much remains unknown about the exact mechanisms of action. FMTs have proven to be an effective treatment for Clostridium difficile (C. diff) infection and treatment-resistant irritable bowel syndrome (IBS) and may have potential in inflammatory bowel diseases [35]. It is likely that different underlying mechanisms contribute to the efficacy of these treatments; for example, specific bile acids regulated by intestinal bacteria are critical for resistance to C. diff infection [36,37]. Targeted administration of efficacious microbes would be ideal to prevent disease, and we are just beginning to identify the specific bacterial species that may regulate diseases from multiple sclerosis to diabetes to norovirus. While it may appear that treating HNoV patients with antibiotics would prove beneficial since antibiotic treatment reduces MNoV titers in mice, it may actually cause more harm than good due to the overall beneficial impact of the microbiome on human health and the potential for increased susceptibility to other viral, fungal, or bacterial infections. Probiotics may be a better therapeutic option, such as adding helpful microbes to a patient’s microbiome to fight infection or as a form of biological vaccine adjuvant. And in the case of NoV, development of drugs that temporarily mitigate the effect of commensal microbes and their metabolites without clearing bacterial populations could prove to be a viable treatment option in the future. 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July 10, 2018 2:27 PM
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Infusion of mesenchymal stromal cells (MSCs) is a promising and increasingly applied therapy for patients who suffer from a variety of inflammatory diseases, including graft-versus-host disease (GvHD), a common and life-threatening complication after allogeneic hematopoietic stem cell transplantation. The therapeutic effect of MSCs is mainly ascribed to their ability to suppress T cells and to support tissue repair. However, clinical response rates in patients with GvHD are limited to 50%, and the determinants for MSC responsiveness are unknown. We recently reported that high frequencies of activated group 3 innate lymphoid cells (ILC3s) before and after allogeneic hematopoietic stem cell transplantation were associated with a lower risk of GvHD. This may be related to IL-22 production by ILC3s, a cytokine important for intestinal epithelial cell homeostasis. In this study, we investigated whether ILC3s may contribute to the therapeutic effect of MSCs by studying the interaction between MSCs and ILC3s in vitro. ILC3s isolated from human tonsils were cocultured with human bone marrow–derived MSCs for 5 d in the presence of IL-2. Coculture with MSCs enhanced the proliferation and IL-22 production of ILC3s. Reciprocally, ILC3s promoted ICAM-1 and VCAM-1 expression on MSCs. For both directions, the activation was mainly mediated by cell–cell contact and by MSC-derived IL-7 and likely by aryl hydrocarbon receptor ligands. Thus, in addition to inhibiting the proliferation of alloreactive T cells, MSCs also promote the expansion and IL-22 production of ILC3s, which may contribute to healthy homeostasis and wound repair in the treatment of various inflammatory conditions in the intestine, including GvHD.
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Scooped by
Gilbert C FAURE
February 2, 2018 8:48 AM
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Scooped by
Gilbert C FAURE
June 17, 2017 8:26 AM
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Rationale Interleukin (IL)-33, a new member of the IL-1 family, is constitutively expressed in epithelial tissues and lymphoid organs and plays an important role in the pathogenesis of allergic disease. However, the role of IL-33 in chronic rhinosinusitis with nasal polyps (CRSwNP) remains unclear.
Objective To investigate the role of IL-33 in the pathophysiology of CRSwNP.
Methods We investigated IL-33 expression and its cellular origins in the nasal polyps (NPs) of human subjects by immunohistochemistry (IHC), quantitative reverse transcription PCR (qRT-PCR), and multiplex cytokine assays. Correlations between IL-33 expression and other inflammatory markers were also explored. To investigate the role of IL-33 in CRSwNP, anti-IL-33 antibody was used in a murine model of CRS.
Results Uncinate process tissues from control (19), CRSsNP (61), CRSwNP (69) and NP tissues (71) were used in this study. Increased expression of IL-33 mRNA and protein in patients with CRSwNP compared with controls was observed. The concentration of IL-33 protein in CRSwNP was positively correlated with the number of neutrophils and the expression of several Th1 and Th17 inflammatory markers, including interferon (IFN)-γ, IL-1β, tumour necrosis factor (TNF)-α, IL-17A, IL-22, and various markers for neutrophil recruitment. However, protein levels of IL-5 and quantity of eosinophils were inversely correlated with levels of IL-33. The expression of tissue inhibitor of metalloproteinase (TIMP)-1 was negatively correlated with IL-33 protein levels, while the expression of matrix metalloproteinase (MMP)-2 and MMP-9 was positively correlated with IL-33 protein levels. In animal studies, IL-33 expression was upregulated in the CRSwNP group compared with controls. Anti-IL-33 treatment reduced the thickness of oedematous mucosa, subepithelial collagen deposition, and infiltration of neutrophils, but infiltration of eosinophils was not reduced. This treatment also inhibited the expression of neutrophilic inflammatory cytokines, but not IL-4. In addition, the expression of intracellular adhesion molecule 1, vascular adhesion molecule 1 and CXCL-2 in the nasal mucosa was suppressed in mice treated with anti-IL-33 antibody.
Conclusions Our data suggest a role for IL-33 in the pathogenesis of CRSwNP via neutrophil recruitment. Therefore, anti-IL-33 may provide a new treatment strategy to target infiltrating neutrophils in CRSwNP.
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Scooped by
Gilbert C FAURE
February 9, 2017 4:56 AM
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Doctors have long understood that antibiotics that protect infants from infection also can disrupt the normal growth of their gut bacteria. However, a new study reveals that the consequences of routine antibiotic use may be deeper and longer lasting than expected. The study, published Feb. 8 in Science Translational Medicine, shows that short-term disruption of gut bacteria makes infant mice more likely to develop pneumonia. It also makes them more likely to die from it.
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Suggested by
Société Francaise d'Immunologie
August 17, 2016 9:08 AM
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Cellular and Molecular Immunology aims to report the dynamic progress being made in China and abroad in immunological research, and welcomes high-quality Research Articles, Reviews and Brief Reports across a broad range of topics including, but not...
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Scooped by
Gilbert C FAURE
December 1, 2015 3:52 AM
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New research shows a network of immune cells helps the appendix play a pivotal role in maintaining digestive health, supporting the theory that the appendix isn’t a redundant organ.
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