Attenuation of allergen-specific immunotherapy for atopic dermatitis by ectopic colonization of Brevundimonas vesicularis in the intestine

Xiaochun Liu; Beilei Xu; Xiaoqiang Xu; Zhifeng Wang; Yang Luo; Yingxia Gao; Shiqi Ling; Ao Wang; Yuan Zhou; Xiaokai Wang; Sean Xiao Leng; Wei Li; Xu Yao

doi:10.1016/j.xcrm.2023.101340

. 2023 Dec 19;4(12):101340. doi: 10.1016/j.xcrm.2023.101340

Attenuation of allergen-specific immunotherapy for atopic dermatitis by ectopic colonization of Brevundimonas vesicularis in the intestine

Xiaochun Liu ^1,⁸, Beilei Xu ^1,⁸, Xiaoqiang Xu ^2,⁸, Zhifeng Wang ^3,⁸, Yang Luo ¹, Yingxia Gao ¹, Shiqi Ling ¹, Ao Wang ¹, Yuan Zhou ¹, Xiaokai Wang ⁴, Sean Xiao Leng ^5,^6,^7,^∗, Wei Li ^2,^∗∗, Xu Yao ^1,^9,^∗∗∗

PMCID: PMC10772585 PMID: 38118418

Summary

Allergen-specific immunotherapy (AIT) has shown beneficial effects against atopic dermatitis (AD); however, the mechanisms and parameters underlying the efficacy of AIT remain unclear. Here, we report that the community structure and function of the oral and gut microbiota are changed in patients with AD undergoing AIT. Transplantation of fecal microbiota from patients who respond well to AIT improves AD-like dermatitis in mice. The abundance of Brevundimonas vesicularis in the gut of AD patients has been found to be positively correlated with disease severity and is decreased following AIT. Furthermore, we find that B. vesicularis from the oral cavity might ectopically colonize the gut of AD patients. In AD model mice, meanwhile, B. vesicularis promotes the skewing of the Treg/Th17 balance toward Th17 polarization and attenuates the efficacy of ovalbumin-specific immunotherapy. Our findings provide potential strategies for the optimization of AIT for AD via the modulation of the gut microbiota.

Keywords: atopic dermatitis, allergen-specific immunotherapy, microbiota, oral cavity, gut

Graphical abstract

Highlights

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The oral and gut microbiota are changed in patients with AD undergoing AIT
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B. vesicularis in the oral and gut microbiota is decreased following AIT
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Oral B. vesicularis may ectopically colonizes the gut of patients with AD
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B. vesicularis promotes Th17 polarization and attenuates the efficacy of AIT

Liu et al. reveal the alteration of oral and gut microbiota in patients with AD undergoing AIT and identify a specific microbe, Brevundimonas vesicularis, that acts as an aggravating factor in AD-induced inflammation and influences the efficacy of AIT.

Introduction

Atopic dermatitis (AD) is a chronic, inflammatory skin disease that affects 10%–30% of children and 3%–5% of adults worldwide.¹^,² AD is characterized by a T helper 2 (Th2)-dominant inflammatory immune deviation with differential inflammation-related contributions from other Th-type cells, such as Th17, Th22, and Th1, and Asian AD patients are characterized by increased infiltration of Th17 inflammation,³^,⁴^,⁵ whereas the function of regulatory T cells (Tregs) is impaired in AD.⁶^,⁷ Although the introduction of many novel drugs, such as biologics and JAK inhibitors, has greatly increased the efficacy of therapy, the treatment of this condition remains difficult, and patients often relapse if therapy is discontinued. Thus, strategies that can reverse the immune deviation and modulate the pathophysiology of AD are urgently needed. Allergen-specific immunotherapy (AIT) can change the progression of allergic diseases and has demonstrated therapeutic efficacy against AD in several clinical trials.⁸^,⁹^,¹⁰^,¹¹ The mechanism may involve the regulation of the balance between allergen-specific immunoglobulin E (IgE) and IgG4 and/or the induction of regulatory T cells (Tregs).¹²^,¹³ However, the therapeutic efficacy of AIT against AD varies among patients, and the parameters influencing the efficacy of AIT need to be further explored.

It has been established that the gut microbiome is involved in the pathogenesis of AD, especially in children.¹⁴^,¹⁵^,¹⁶^,¹⁷ Compared with healthy individuals, patients with AD have lower gut microbiota diversity¹⁸^,¹⁹ but a greater abundance of several microbes, such as Escherichia coli, Staphylococcus, and Blautia.¹⁶^,²⁰^,²¹ Probiotics have been used for the alleviation of AD for decades, with combinations of several strains of Lacticaseibacillus and/or Bifidobacterium having demonstrated both therapeutic and preventive effects.²²^,²³ Gut and oral microbiota have been associated with the efficacy of AIT in several allergic diseases. Gut microbiota diversity is increased during sublingual immunotherapy (SLIT) in peanut-allergic adults,²⁴ while a high ratio of the salivary bacterium Prevotella is associated with clinical remission in patients with pollinosis who undergo SLIT.²⁵ The gut microbiota can modify the levels of short-chain fatty acids (SCFAs) in the gut and regulate Treg induction, thus participating in the pathogenesis of several inflammatory diseases.²⁶^,²⁷ However, neither the precise role of the gut microbiome in AD and AIT nor the underlying mechanisms have been fully explored to date.

The ectopic colonization of the gut by oral microbiota is a common phenomenon in both physiological and pathophysiological conditions.²⁸^,²⁹ Interactions between the oral and gut microbiota can reshape the microbial ecosystem of the intestine and finally modulate physiological functions, which is referred to as the “oral-gut axis.”³⁰ It has been reported that the ectopic colonization of the intestine by Klebsiella spp. from the oral cavity contributes to the exacerbation of inflammatory bowel disease.³¹ Nevertheless, the associated mechanisms remain unclear, although the results of some studies have suggested that microbes from the oral cavity induce the production of pro-inflammatory cells and mediators, thus modulating the immune responses.³¹^,³² We have previously demonstrated that the site specificity of the oral and gut microbiota is decreased in patients with AD compared with that in healthy individuals²¹; however, whether microbial translocation occurs between the oral cavity and the gut in these patients remains unknown.

In this study, we explored the involvement of the oral and gut microbiota in AIT for AD. We found that the community structure and function of the oral and gut microbiota were altered in AD patients undergoing AIT. Brevundimonas vesicularis in the gut was related to the disease severity and B. vesicularis from the oral cavity colonized the gut of patients with AD. In AD model mice, meanwhile, intragastric B. vesicularis administration exacerbated AD-like dermatitis and promoted the skewing of the Treg/Th17 balance toward Th17 polarization, consequently attenuating the efficacy of ovalbumin (OVA)-specific immunotherapy against AD.

Results

The improvement in AD following AIT is accompanied by alterations in the oral and gut microbiota

We first explored the effects of house dust mite (HDM)-specific AIT on AD (Figure 1A). Patient information at baseline and post treatment is presented in Table S1. After 6 months of treatment, the Scoring Atopic Dermatitis (SCORAD) index and Eczema Area and Severity Index (EASI) scores of patients with AD were significantly decreased compared with those at baseline, and the improvement persisted for 12 months of treatment. The pruritus index, sleep quality index, and Dermatology Life Quality Index (DLQI) scores were significantly reduced at both 6 and 12 months of treatment (nearly half of baseline at 6 months). The improvement was more pronounced at 6 months than at 12 months. The eosinophil count was significantly decreased after 12 months of AIT compared with that at baseline (Figure 1B and Table S1). Collectively, our results revealed that AIT exerted therapeutic effects among AD patients with HDM sensitization.

The oral and fecal microbiota of the AD patients undergoing AIT were then analyzed using 16S rRNA sequencing (Figure 1A). The oral microbiota of the patients at 6 months of treatment diverged from that at baseline as observed in the unweighted UniFrac principal coordinates analysis; moreover, the difference between 12 months and 6 months of treatment was smaller than that between 6 months and baseline or between 12 months and baseline (Figures 1C and 1D). At 12 months of treatment, the gut microbiota of the patients clustered separately from that at baseline and 6 months of treatment, and the difference between the 6-month time point and baseline was smaller than that between the 12-month time point and baseline or between the 12-month and 6-month treatment time points (Figures 1C and 1D). Similarly, the β-diversity assessment of the oral microbiota based on unweighted UniFrac was significantly different among the three groups, and the gut microbiota of the patients at 12 months of treatment differed from that at baseline (Figure S1C). Analysis based on weighted UniFrac distances showed similar but weak segregation among the three groups for both the oral and gut microbiota (Figures S1A, S1B, and S1D). These data indicated that the pattern of change was different between the oral and gut microbiota. No significant difference in the α-diversity of the microbiota from either the oral or stool samples was observed before and after AIT, except for a significant increase at the amplicon sequence variant (ASV) level for the gut microbiota at 12 months of treatment compared with that at baseline and 6 months of treatment (Figure 1E). For functional prediction analysis, there were alterations in amino acid metabolism-related and lipid metabolism-related pathways in the oral microbiota at 6 months of treatment (Figure S1E). For example, the pathways involved in lysine degradation and fatty acid metabolism were enriched at baseline, but the pathways for arginine and proline metabolism were enriched at 6 months. A greater number of functional pathways were changed in the gut microbiota at 12 months of treatment compared with that at baseline. Specifically, there was an enrichment of pathways for tryptophan metabolism, butanoate metabolism, and propanoate metabolism (Figure S1E), suggesting that pathways associated with regulatory immune responses might be involved in AIT.

Collectively, the results indicated that AIT exerted therapeutic effects in patients with AD, concomitant with extensive alterations in the structure and function of both the oral and gut microbiota.

Transplantation of fecal microbiota from patients undergoing AIT improves AD-like dermatitis in mice

We next performed fecal microbiota transplantation (FMT) to confirm the involvement of the gut microbiota in the effects of AIT using a mouse model of MC903-induced AD. Mice were intragastrically administered with antibiotics before application of MC903. Fecal microbiota from healthy controls, untreated AD patients, or patients showing a marked improvement following AIT (those that achieved a 50% decrease in the EASI) was administered intragastrically to AD mice (Figure 2A). Intragastric PBS administration served as the control, which was subjected to the same paradigm as the FMT groups. The microbial communities in the mice after different FMT treatments clustered separately compared with pre-FMT (Figure S2D). There was a markedly increased proportion of gut microbiota from the donors at the genus level after FMT, indicating colonization of transferred microbiota after FMT (Figure S2E). Mice administered MC903 displayed erythema, edema, ear scaling, increased ear thickness, and increased levels of total IgE (Figures 2B, 2C, and 2E); however, these effects were markedly decreased after the transplantation of fecal microbiota from patients who showed a marked improvement following AIT (Figures 2B–2E). No significant difference in skin inflammation was detected between mice that received fecal microbiota from untreated AD patients and those treated with PBS. AD model mice that received fecal microbiota from healthy controls only showed a significant decrease in the thickness of the epidermis (Figures 2B–2E). The proportion of CD4⁺CD25⁺Foxp3⁺ Tregs in the spleen of AD mice was reduced after the transplantation of fecal microbiota from AD patients; in contrast, the proportion of Tregs was higher in the central lymph nodes (CLNs), mesenteric lymph nodes (MLNs), and spleens of AD mice receiving fecal microbiota from patients who showed a good response to AIT than in those of model mice receiving PBS or fecal microbiota from untreated patients (Figure 2F). Taken together, these results demonstrated that the transplantation of fecal microbiota from patients with AD who responded well to AIT alleviated AD-like dermatitis in mice and increased the Treg proportion.

Abundance of B. vesicularis in the oral and gut microbiota is decreased after AIT

We next characterized the changes occurring in the composition of the oral and gut microbiota of patients with AD after AIT. The ten most abundant phyla are shown in Figure 3A. The composition of the oral microbiota changed after both 6 and 12 months of treatment; however, no significant difference in microbial composition was observed between the two time points. For example, the abundance of Actinobacteria and Fusobacteria increased after 6 months of treatment and remained at a similarly high level until 12 months of treatment (Figures 3A and S3A; Data S1). In contrast, the composition of the gut microbiota showed a progressive change with the continuation of therapy. The abundance of the most dominant phyla in the gut microbiota, Bacteroidetes and Firmicutes, was gradually decreased and increased, respectively. These results were consistent with the observed changes in the diversity of the oral and gut microbiota (Figures 1C and 1D). At the genus level, the patterns of microbial enrichment in the two habitats differed before and after treatment. Notably, the abundances of Stenotrophomonas and Brevundimonas were significantly reduced at both 6 and 12 months of treatment (Figure 3B and Data S1). To validate the characteristics of the oral and gut microbiota at the species level, we identified the discriminatory taxa at the ASV level. The results showed that B. vesicularis was the only species that displayed significantly decreased abundance after both 6 and 12 months of treatment in both the oral cavity and gut (Figures 3C and S3B; Data S1). Collectively, our results revealed the alterations occurring in the microbial composition and specific microbes of the oral and gut microbiota with AIT and further showed that the abundance of B. vesicularis was decreased in both habitats after immunotherapy.

B. vesicularis from the oral cavity colonizes the gut of patients with AD

We have previously reported that the oral and gut microbiota of patients with AD display decreased site specificity.²¹ Accordingly, we next compared the microbial communities of the two habitats in patients with AD after AIT. Analysis based on unweighted UniFrac distances showed that the distance between the oral and gut microbiota of AD patients was significantly increased after AIT (Figure 4A). Compared with baseline, the numbers of shared genera and ASVs in oral and stool samples from single individuals were significantly reduced at both 6 and 12 months of treatment (Figure 4B). These findings suggested that the oral and gut microbiota became more distinct after AIT. Because of the close distance between the gut and oral microbiota in untreated AD patients, we hypothesized that there might be ectopic colonization of oral microbes in the gut. To confirm this possibility, we analyzed the correlation between the oral and gut microbiota in patients with AD. The results showed that most of the genera were positively correlated with the microbes of their respective habitats. However, Brevundimonas in the stool was strongly positively correlated with the genera of the oral cavity, but not the gut, which suggested that Brevundimonas in the stool might have originated in the oral cavity. In contrast, Brevundimonas from the oral cavity was found to be positively correlated with other genera in the oral microbiota but negatively correlated with several gut-specific genera, such as Bifidobacterium, which has been reported to be one of the probiotics in AD (Figure 4C). We further analyzed the correlation of the abundance of B. vesicularis between the two habitats and identified a significant positive correlation between the two body sites at baseline (r = 0.582, p = 1.81e−05; Figure 4D). Collectively, our data suggested that B. vesicularis from the oral cavity might have ectopically colonized the gut of patients with AD and further implied that the ecological niches of the oral cavity and gut recovered after AIT.

B. vesicularis is associated with AD-related clinical parameters

Next, to validate the involvement of B. vesicularis in AD, we analyzed the correlation between the abundance of this bacterium and AD-related clinical parameters using mixed-effects models. The results showed that AD severity, as evaluated by SCORAD index and EASI scores, was highly positively correlated with the abundance of B. vesicularis in both the oral cavity and gut, although the correlation was significant only in the gut. The abundance of B. vesicularis in the oral cavity and gut showed a significant positive correlation with the eosinophil count. Additionally, B. vesicularis was significantly positively correlated with the itch index and DLQI only in the gut. No significant correlation was detected between B. vesicularis and the sleep index (Figure S4). Combined, our results suggested that the abundance of B. vesicularis, especially in the gut, was positively correlated with the severity of AD.

Intragastric B. vesicularis aggravates MC903-induced AD-like dermatitis in mice

To further explore the role of B. vesicularis in AD, B. vesicularis was intragastrically administered to antibiotic-pretreated mice with MC903 + OVA-induced AD (Figures 5A and S5A). The AD mice exhibited evident skin inflammation manifesting as erythema, edema, and ear scaling, accompanied by greater ear thickness (Figures 5B–5E), increased eosinophil infiltration, and elevated levels of total serum IgE (Figures 5F and 5G). These effects were exacerbated following the administration of B. vesicularis, while the expression of thymic stromal lymphopoietin in the skin lesions was also significantly increased (Figures 5B–5G and S5B). However, no significant difference in morphology or total IgE levels was observed in the model mice treated with B. vesicularis alone, although the level of eosinophil infiltration was slightly elevated (Figures 5B–5G).

CD103⁺ dendritic cells (DCs) in the intestine have been shown to promote the expansion of Foxp3⁺ Tregs and are regarded as regulatory DCs (DCregs).³³ Compared with PBS treatment, B. vesicularis administration significantly decreased the percentage of CD103⁺ DCs in both the CLNs and MLNs of mice, irrespective of whether MC903 + OVA was applied (Figure 5H). B. vesicularis moderately induced the expression of CD86 and major histocompatibility complex class II (MHCII) on CD11c⁺ DCs in the CLNs and MLNs of AD model mice (Figure S5C). In addition, the administration of B. vesicularis alone reduced the expression of programmed cell death-1 ligand (PD-L1) in the CLNs, similar to that seen with MC903 + OVA application (Figure S5C). CD11c⁺ DCs isolated from the spleens were stimulated with live or heat-killed B. vesicularis for 24 h in vitro. Live B. vesicularis administration resulted in significantly increased levels of transforming growth factor β1 (TGF-β1) and interleukin-6 (IL-6) in the supernatant of culture, while the heat-killed bacteria-treated DCs selectively secreted a great amount of IL-6 (Figure 5I). Collectively, these results suggested that B. vesicularis inhibited the tolerogenic capacity of DCregs by inducing the expression of co-stimulatory molecules and downregulating the level of PD-L1, as well as increasing the expression of pro-inflammatory factors.

We further assessed CD4⁺ Th cell polarization after B. vesicularis treatment. The proportion of CD4⁺CD25⁺Foxp3⁺ Tregs was decreased in the spleens of mice treated with B. vesicularis; however, no significant difference in the Treg proportion was seen in the CLNs and MLNs between B. vesicularis-treated mice and the controls (Figure S5D). Notably, compared with control mice, animals receiving B. vesicularis showed increased expansion of CD4⁺RORγt⁺ Th17 cells and an elevated Th17/Treg ratio in the CLNs, MLNs, and spleens in both the MC903 + OVA-treated and vehicle-treated groups (Figures 5J–5L and S5E), indicative of a skewing of the Treg/Th17 cell balance toward Th17 polarization. CD11c⁺ DCs isolated from the MLNs or spleens were stimulated with live or heat-killed B. vesicularis and then co-cultured with naive CD4⁺ T cells isolated from the spleens for 4 days. CD4⁺ T cells co-cultured with B. vesicularis-treated DCs differentiated into a greater number of Th17 cells than Tregs (Figures S5G and S5H), and the live B. vesicularis-treated co-culture system produced significantly more IL-17A than the control system (Figure S5I). Heat-killed B. vesicularis-treated DCs also promoted the induction of Th17 cells and inhibited the expansion of Tregs (Figures S4G and S4H). We did not find any difference in the frequencies of CD4⁺IFN-γ⁺ Th1 cells or CD4⁺IL-4⁺ Th2 cells between B. vesicularis-treated mice and the controls, except for a modest increase in Th1 cell proportions in AD mice receiving B. vesicularis compared with those receiving PBS (Figure S5F).

To verify that the effects of B. vesicularis on skin inflammation were specific rather than a generic bacterial response, we isolated three common gut commensal microbes, Bacteroides uniformis, Ruminococcus gnavus, and Prevotella copri, that were decreased in abundance after AIT from the patients’ stools. All three of the commensal bacteria-treated DCs were unable to increase the Th17/Treg ratio in the co-culture system (Figures S6A and S6B). Furthermore, we selected one of the bacterial strains, B. uniformis, and found that B. uniformis-treated AD mice did not exhibit more severe morphological appearance, greater ear thickness, and higher levels of total IgE (Figures S6C–S6F). Likewise, the decreased percentage of CD103⁺ DCs and the increased Th17/Treg ratio observed in B. vesicularis-treated AD mice were not found in the AD mice intragastrically administered with B. uniformis (Figures S6G–S6J).

Taken together, our findings showed that B. vesicularis exacerbated skin inflammation and specifically promoted the skewing of the Treg/Th17 cell balance toward Th17 polarization in AD mice.

B. vesicularis attenuates AIT efficacy in AD mice

To verify the pro-inflammatory effect of B. vesicularis in AIT, an OVA-specific immunotherapy mouse model was established by the subcutaneous administration of OVA and aluminum hydroxide to AD mice (Figure 6A). Redness, scaling, ear swelling, and eosinophil infiltration levels were significantly lower in AD mice subjected to OVA immunotherapy than in those treated with MC903 + OVA alone. A slight reduction in total IgE and OVA-specific IgE levels was found in the OVA immunotherapy group. When the AD mice undergoing immunotherapy were administered B. vesicularis intragastrically before and during treatment, the improvement in inflammation was significantly abrogated, indicating that B. vesicularis interfered with the therapeutic effect of OVA-specific immunotherapy (Figures 6B–6F). Consistent with our previous results, the intragastric application of B. vesicularis alone did not induce visible AD-like dermatitis in normal mice (Figures 6B–6F). Our results further showed that AIT significantly increased the percentage of CD103⁺ DCs in both the CLNs and MLNs in AD model mice. However, compared with the OVA immunotherapy group, AD mice subjected to AIT with the intragastric administration of B. vesicularis exhibited fewer CD103⁺ DCs in both the CLNs and MLNs (Figure 6G), accompanied by a decrease in PD-L1 expression in the CLNs and an increase in CD86 expression in the MLNs (Figure 6H). As expected, in mice receiving AIT, the intragastric administration of B. vesicularis markedly increased the percentage of Th17 cells and the Th17/Treg ratio in the CLNs, MLNs, and spleens, compared with that seen with intragastric PBS administration (Figures 6I, S7A, and S7B). Moreover, intragastric B. vesicularis administration reversed the AIT-induced expansion of CD4⁺CD25⁺Foxp3⁺ Tregs in the CLNs to levels comparable to those seen in the AD group (Figure S7A). We also found that intragastric B. vesicularis administration reversed the OVA immunotherapy-induced reduction in Th1 cell proportions in the spleen (Figure S7C), possibly due to the high production of interferon-γ (IFN-γ) induced by B. vesicularis (Figure S5I). These results indicated that B. vesicularis treatment strongly skewed the Th17/Treg ratio, thereby attenuating the efficacy of AIT in AD mice.

Discussion

The gut microbiota has been strongly implicated in the pathogenesis of AD¹⁴^,¹⁵^,¹⁶^,¹⁷^,³⁴; however, whether it is involved in the effect of AIT in AD remains unclear, as does the putative underlying mechanism. In this study, we revealed that the composition and function of the oral and gut microbiota were altered in patients with AD who underwent AIT. B. vesicularis, which might ectopically colonize the gut from the oral cavity, was positively correlated with AD severity and played a crucial role in the exacerbation of AD-induced inflammation. B. vesicularis also attenuated the efficacy of AIT in AD model mice by promoting the skewing of the Treg/Th17 balance toward Th17 polarization. We report that the oral and gut microbiota can modulate the responses to AIT against AD and identified a specific microbe, B. vesicularis, that acted as an aggravating factor in AD-induced inflammation and influenced the efficacy of AIT. Our results provided potential strategies for improving the efficacy of immunotherapy via the modulation of the gut microbiota.

The mechanism underlying the effect of AIT is not fully understood. The skewing of allergen-specific effector T cells toward a regulatory phenotype is considered crucial for successful AIT.¹² Allergen-specific Tregs and regulatory B cells orchestrate the following: a general immunoregulatory response, including the suppression of cytokine production by inflammatory DCs; a reduction in effector Th1, Th2, and Th17 cell numbers; a decrease in the allergen-specific IgE/IgG4 ratio; and suppression of the migration of mast cells, basophils, eosinophils, and effector T cells.¹² Although the gut microbiota has been associated with the efficacy of AIT in patients with food allergies,²⁴ the role and mechanism of the gut microbiota in AIT remains largely unknown. It has been reported that the transplantation of fecal microbiota from healthy mice to AD mice ameliorates AD-related allergic responses, results in the restoration of the gut microbiota to the donor state, regulates the Th1/Th2 balance via Treg signals, and leads to increased levels of SCFAs.³⁵ The increased production of propionic acid by intestinal microbiota stabilizes IL-10 expression in B cells, which promotes the efficacy of SLIT in mice with allergic rhinitis.³⁶ In our study, the transplantation of fecal microbiota from patients with AD who responded well to AIT alleviated AD-like symptoms in mice and induced the expansion of Tregs. The gut microbiota of AD patients undergoing AIT differed from that of untreated patients in both composition and function, while the pathways for tryptophan metabolism, butanoate metabolism, and propanoate metabolism were enriched in the gut microbiota after 1 year of AIT. SCFAs such as butyrate and propionate exert anti-inflammatory effects via Treg induction.³⁷^,³⁸^,³⁹ Fang et al.⁴⁰^,⁴¹ reported that the oral administration of Bifidobacterium longum and Limosilactobacillus reuteri attenuated AD-related inflammation by remodeling gut microbial composition and inducing the production of tryptophan metabolites. In our study, the increase in tryptophan and SCFA metabolism might result in Treg production and the amelioration of AD-related inflammation, thus promoting the efficacy of AIT. Changes in microbial metabolites in the gut of patients with AD after AIT merits further investigation.

It has been shown that an increase in the abundance of several bacteria (i.e., Staphylococcus, E. coli, and Klebsiella pneumoniae) in the gut plays a part in the aggravation of AD symptoms.²⁰^,⁴²^,⁴³ In the present study, B. vesicularis was identified as an aggravating factor for AD. B. vesicularis is a gram-negative rod bacterium reported to be a causal agent of nosocomial infections and is regarded as one of the emerging global opportunistic pathogens.⁴⁴ It has been reported that a combination of three species, including B. vesicularis, is associated with the allergic or non-allergic asthma phenotype.⁴⁵ B. vesicularis was the only species in the oral cavity and gut that was consistently and significantly decreased after 6 and 12 months of immunotherapy in our study and was closely correlated with the exacerbation of AD. The abundance of B. vesicularis in the gut microbiota was decreased after AIT, which was accompanied by the recovery of site specificity. We hypothesized that a proportion of B. vesicularis transmigrated from the oral cavity to the gut in patients with AD. Consistent with this hypothesis, we found that Brevundimonas in the stool was positively correlated with the genera in the oral cavity rather than with those in the gut, and a positive correlation with the abundance of B. vesicularis was identified between the two habitats. The findings of ectopic colonization of the intestine by B. vesicularis in the patients with AD remain to be further verified, as 16S rRNA sequencing analysis has its limitations in tracing the source of a certain bacterial taxa from one habitat to another. It has been reported that the unweighted UniFrac distance between the oral and gut microbiota of AD patients is decreased compared with that of healthy individuals,²¹ which suggests that microbiota may translocate between the oral cavity and the gut. Ectopic colonization is most commonly reported in inflammatory bowel disease³⁰^,³¹^,³²; however, the mechanisms underlying how the colonization of the gut by oral bacteria initiates intestinal inflammation remain unclear. Ectopic colonization by oral pathobionts may directly activate mucosal inflammatory responses or serve as cognate antigens for T cells that have transmigrated from the oral cavity,³² thereby exacerbating colitis. In the present study, the changes in the oral microbiota in AD may have disturbed the microecology of the oral cavity, leading to weakened physical and/or chemical compartmentalization between oral and intestinal mucosa; consequently, pro-inflammatory bacteria, such as B. vesicularis, could overcome the barriers between the oral cavity and the gut and translocate into the latter.

Our study further demonstrated that B. vesicularis promoted the skewing of the Treg/Th17 balance toward Th17 polarization, thereby exacerbating skin inflammation, which was alleviated by OVA-specific AIT in AD mice. CD103⁺ DCs in the gut might have played a decisive role in the B. vesicularis-induced immune response. CD103⁺ DCs of the intestinal mucosa are essential for tolerance to commensal bacteria. These cells originate in the lamina propria and migrate to the MLNs where they drive the differentiation of gut-homing Foxp3⁺ Tregs.⁴⁶^,⁴⁷ A mixture of probiotics can modulate the structure of the gut microbiota and alleviate AD symptoms by promoting the expansion of intestinal CD103⁺ DCs and Treg differentiation,⁴⁸ which is consistent with the effect of AIT in AD model mice seen in our study. The reduced abundance of B. vesicularis allows the expansion of CD103⁺ DCs in the MLNs and CLNs and their tolerogenic potential, which may contribute to the protective effect of immunotherapy. AD is a highly heterogeneous disease that is characterized by Th2-dominant inflammation, whereas Th17-type and Th22-type inflammation also differentially contribute to the pathogenesis of AD. It is noteworthy that Asian patients with AD have a substantial proportion of Th17-type inflammation.⁴ Thus, attenuation of Th17 polarization and impairment of Th17/Tregs would promote the efficacy of AIT for AD. OVA-induced AD inflammation in mice can be ameliorated by inhibiting IL-17 secretion from Th17 cells.⁴⁹ IL-17A downregulates the expression of genes involved in epidermal barrier formation⁵⁰ and serves as an inducer for Th2 immune responses in AD.⁵¹ There is a Th17/Treg imbalance in AD, and the Th17/Treg ratio is positively correlated with AD severity and serum IgE levels.⁵² Several studies have reported that the Th17/Treg ratio is decreased during AIT.⁵³^,⁵⁴ IL-17 produced by Th17 cells reduces Treg concentrations, thus eliminating the therapeutic effects of oral tolerance promoted by AIT in mice.⁵⁵ Consistent with previous studies, we found that the number of Tregs was increased in AD mice undergoing immunotherapy. B. vesicularis inhibited AIT-induced Treg expansion in the CLNs, induced the polarization of Th17 cells, and increased the Th17/Treg ratio, accompanied by the induction of Th1 cells, both in vivo and in vitro. The exact mechanism by which B. vesicularis regulates the Th17/Treg balance remains incompletely understood. Whether the effects of B. vesicularis are due to a transient or long-term colonization remains unclear. B. vesicularis promotes the secretion of TGF-β and IL-6 by DCs. It is known that TGF-β can upregulate the expression of RORγt in the presence of IL-6, therefore inducing the differentiation of CD4⁺ T cells toward Th17 polarization.⁵⁶ Heat-killed B. vesicularis is sufficient to induce high levels of IL-6, which might also help in suppressing Treg expansion induced by TGF-β.⁵⁶^,⁵⁷ Notably, although B. vesicularis alone altered the number and function of CD103⁺ DCs and affected the polarization of Th cells to various degrees in healthy mice, these effects were not enough to induce either dermatitis or systemic allergic inflammation or to induce Th17 cytokines (Figure S5E). These data indicated that there might be self-regulation in the local microenvironment or adjustment between B. vesicularis and other bacteria under physiological conditions.

In conclusion, our study revealed the specific changes occurring in the oral and gut microbiota of patients with AD undergoing AIT and provided evidence for the ectopic colonization of the gut by oral microbiota in AD. Future studies should explore the therapeutic potential by modulating the gut and/or oral microbiome through the “oral-gut-skin axis” in patients with AD who are receiving immunotherapy.

Limitations of the study

The exact mechanism by which B. vesicularis regulates the Th17/Treg balance needs further exploration. The present study provided preliminary evidence for the ectopic colonization of the gut by oral microbiota in patients with AD merely using 16S rRNA sequencing analysis; however, further studies are needed to validate that B. vesicularis in the gut of AD patients originate from the oral cavity. We could not exactly validate the mechanical correlation between the alteration of B. vesicularis and the efficacy of AIT. The 16S rRNA sequencing analysis does not ensure accuracy of functional predictions and strain-level analysis. Shotgun metagenomic sequencing can be utilized regarding functional annotation and potential mechanisms by which oral and gut microbiota are involved in AD.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies

Purified Rat Anti-Mouse IgE (Clone R35-72)	BD Biosciences	Cat # 553413; RRID: AB_394846
Purified Mouse IgE, κ Isotype Control Standard (Clone C48-2)	BD Biosciences	Cat # 557080; RRID: AB_396578
Biotin Rat Anti-Mouse IgE (Clone R35-118)	BD Biosciences	Cat # 553419; RRID: AB_394850
Mouse anti-Ovalbumin IgE	Bio-Rad	Cat # MCA2259; RRID: AB_2285753
Anti-mouse CD8a PerCP/Cy5.5 (Clone 53-6.7)	BioLegend	Cat # 100734; RRID: AB_2075238
Anti-mouse CD4 FITC (Clone GK1.5)	eBioscience	Cat # 11-0041-82; RRID: AB_464892
Anti-mouse CD3e PE-CYN7 (Clone 145-2C11)	eBioscience	Cat # 25-0031-82; RRID: AB_469572
Anti-mouse IFN-γ Brilliant Violet 510™ (Clone XMG1.2)	BioLegend	Cat # 505842; RRID: AB_2734494
Anti-mouse IFN-γ PE (Clone XMG1.2)	eBioscience	Cat # 17-7311-82; RRID: AB_466193
Anti-mouse IL-4 APC (Clone11B11)	eBioscience	Cat # 17-7041-82; RRID: AB_469494
Anti-mouse IL-17A Brilliant Violet 605™ (Clone TC11-18H10.1)	BioLegend	Cat # 506927; RRID: AB_11126144
Anti-mouse RORγt Brilliant Violet 421™ (Clone Q31-378)	BD Biosciences	Cat # 562894; RRID: AB_2687545
Anti-mouse CD25 APC (Clone PC61.5)	eBioscience	Cat # 17-0251-82; RRID: AB_469366
Anti-mouse FOXP3 PE (Clone FJK-16S)	eBioscience	Cat # 12-5773-82; RRID: AB_465936
Anti-mouse CD274 (B7-H1, PD-L1) Brilliant Violet 605™ (Clone 10F.9G2)	BioLegend	Cat # 124321; RRID: AB_2563635
Anti-mouse CD274 PE-CYN7 (Clone MIH5)	eBioscience	Cat # 25-5982-82; RRID: AB_2573509
Anti-mouse I-A/I-E Pacific Blue™ (Clone M5/114.15.2)	BioLegend	Cat # 107620; RRID: AB_493527
Anti-mouse I-A/I-E Alexa Fluor® 700 (Clone M5/114.15.2)	BioLegend	Cat # 107622; RRID: AB_493727
Anti-mouse CD86 APC (Clone GL1)	eBioscience	Cat # 17-0862-82; RRID: AB_469419
Anti-mouse CD86 FITC (Clone GL1)	eBioscience	Cat # 11-0862-82; RRID: AB_465148
Anti-mouse CD11c PE (Clone N418)	BioLegend	Cat # 117308; RRID: AB_313777
Anti-mouse CD103 FITC (Clone 2E7)	BioLegend	Cat # 121420; RRID: AB_10714791
FcR Blocking Reagent, mouse	Miltenyi Biotec	Cat # 130-092-575

Biological samples

Human peripheral blood	Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College	N/A
Stool samples from AD patients	Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College	N/A
Oral swabs from AD patients	Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College	N/A

Bacterial and virus strains

Brevundimonas vesicularis strain	CGMCC	Cat # 1.3355
Bacteroides uniformis strain	This paper	N/A
Ruminococcus gnavus strain	This paper	N/A
Prevotella copri strain	This paper	N/A

Chemicals, peptides, and recombinant proteins

Streptomycin sulfate	MedChemExpress	Cat # HY-B0472
Ampicillin sodium	MedChemExpress	Cat # HY-B0522A
Calcipotriol (MC903)	LEO Pharma	Cat # H20150664
Recombinant Mouse IL-2	R&D Systems	Cat # 402-ML-020
Cell Stimulation Cocktail (plus protein transport inhibitors)	Thermo Fisher Scientific	Cat # 00-4975-93
Foxp3/Transcription Factor Staining Buffer Set	eBioscience	Cat # 00-5523-00
Fixation/Permeabilization Concentrate	Thermo Fisher Scientific	Cat # 00-5123-43
Fixation/Permeabilization Diluent	Thermo Fisher Scientific	Cat # 00-5223-56
Ovalbumin	Sigma-Aldrich	Cat # A5503
Ovalbumin (Biotin)	USBiological	Cat # O8075-01
Streptavidin HRP	BD Biosciences	Cat # 554066; RRID: AB_2868972
Anti-PE MicroBeads	Miltenyi Biotec	Cat # 130-048-801
CD4 (L3T4) MicroBeads, mouse	Miltenyi Biotec	Cat # 130-117-043
TRIzol™ Reagent	Thermo Fisher Scientific	Cat # 15596018
Lipopolysaccharides from Escherichia coli O111:B4	Sigma-Aldrich	Cat # L4391

Critical commercial assays

FastPure Host Removal and Microbiome DNA Isolation Kit	Vazyme	Cat # DC501-01
HiScript II Q RT SuperMix for qPCR	Vazyme	Cat # R222-01
AceQ qPCR SYBR Green Master Mix	Vazyme	Cat # Q141-02
Mouse TGF-β1 ELISA Kit	Fcmacs Biotech	Cat # FMS-ELM029
Mouse IL-6 ELISA Kit	Fcmacs Biotech	Cat # FMS- ELM006
Mouse IL-17A ELISA Kit	Fcmacs Biotech	Cat # FMS-ELM016
Mouse IFN-γ ELISA Kit	Fcmacs Biotech	Cat # FMS-ELM027

Deposited data

Oral swabs and stool 16S rRNA sequencing data	This paper	ID: PRJEB56808; https://www.ebi.ac.uk/ena/browser/view/

Oligonucleotides

qPCR primer sequences	This paper	See Method Details

Software and algorithms

R v3.4.0	R	https://www.r-project.org/
QIIME 2 (2020.2)	QIIME 2	https://qiime2.org/
FlowJo version 10.4	TreeStar	https://www.flowjo.com/solutions/flowjo
GraphPad Prism 8.0 version 8.0	GraphPad Software	https://www.graphpad.com/scientific- software/prism; RRID: SCR_002798

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Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to, and will be fulfilled by, the lead contact, Xu Yao (dryao_xu@126.com).

Materials availability

This study did not generate new unique reagents.

Data and code availability

The 16S rRNA sequencing data reported in this paper have been deposited in the European Bioinformatics Institute (EMBL-EBI), and are publicly available as of the date of publication. Accession numbers are listed in the Key resources table. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Experimental model and study participant details

Human studies

In total, AD 47 patients with HDM sensitization were recruited at the Department of Allergy and Rheumatology, Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College from October 2017 to May 2020 (see Table S1). All the patients fulfilled the diagnostic criteria of Hanifin & Rajka for AD, with a history of clinical exacerbation after exposure to HDM and a value of >3.5 kU/L for HDM specific-IgE measured by ImmunoCap System (Phadia, Uppsala, Sweden). All the patients received repeated subcutaneous injections of dust-mite therapeutic vaccines (Alutard SQ, ALK, Denmark). The procedure had two stages: initial buildup period and maintenance period. The initial buildup period lasted 4 to 5 months, and it comprised weekly vaccine injection at gradually increasing doses until the recommended maintenance dose (1.0 mL, 100,000 SQ-U/mL) was reached. The maintenance dose was administered at 4 to 6 weeks intervals. The patients undergoing AIT were followed up at 6 and 12 months of treatment initiation. None of the subjects had oral or intestinal diseases other than AD at the time of sampling, and none of the subjects had systemic diseases or received antibiotics treatment within 6 months before sample collection. Samples of the oral cavity and stool were collected from each patient. The subjects were instructed to avoid brushing teeth and eating food for 2 h prior to oral sampling. Oral samples were collected by rubbing the buccal mucosa, keratinized gingiva, supragingival plaque, and tongue dorsum with a swab, as reported previously.²¹ Stool samples were self-collected, stored on ice, and sent to the laboratory within 1 h of defecation. Clinical assessment was performed by the same investigator throughout the study period, utilizing SCORAD index, EASI, pruritus index (from SCORAD index), sleep quality index (from SCORAD index), and Dermatology Life Quality Index (DLQI). Peripheral blood was obtained for preparation of serum and analysis of blood cell counts. For fecal transplantation of microbiota, stool from AD 5 patients, 5 patients showing a marked improvement following 12 months of AIT (achieved a 50% decrease in the EASI), and 5 healthy volunteers were collected and stored at −80°C (see Table S2). The study was approved by the ethics committee of the Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College [ethical approvals: 2016-KY-023], and the informed written consent was obtained.

Animal studies

Animal studies were approved by the Animal Welfare Ethics Review Committee of the Institute of Dermatology, Chinese Academy of Medical Sciences. Six to eight-week-old female BALB/c mice were purchased from the Laboratory Animal Center of the Nanjing Medical University (Nanjing, Jiangsu, China). All the mice were maintained with a 12-h light/dark cycle at 19°C–24°C under specific pathogen-free condition. A standard extruded pellet diet and water were supplied unlimited. All the mice were randomly assigned for experiments.

Method details

16S rRNA gene sequencing and analysis

DNA extraction and 16S rRNA sequencing

Total genome DNA from the oral cavity and stool samples was extracted by Novogene Bioinformatics Technology (Beijing, China) using a previously described method,²¹ and sequenced the V3 to V4 region of bacterial 16S rRNA genes in 2 × 250 bp paired-end (PE) mode on the Illumina HiSeq2500 platform (Illumina, USA) according to the manufacturer’s instructions. The V3–V4 region of the 16S rRNA genes was amplified using the specific primer pair 341F/806R with barcoding. Sequencing libraries were generated using the TruSeq DNA PCR-Free Sample Preparation Kit (Illumina) following the manufacturer’s recommendations, and index codes were added.

16S sequencing data analysis

After quality control and removal of chimeric sequences, the paired end sequences were joined by FLASH (v1.2.7). To eliminate the influence of sequencing depth fluctuations, we downsized the number of reads to 50000 for each sample. Three oral swab samples (6 months of AIT) were excluded from the subsequent analysis due to an insufficient number of reads. Paired sequences were input into QIIME 2 (2020.2). Sequences were quality filtered and denoised using Deblur (q2-deblur) with parameters ‘--p-trim-length 400’ to generate ASVs. All ASVs were aligned with mafft⁵⁸ (via q2-alignment) and used to construct a phylogeny with fasttree⁵⁹ (via q2-phylogeny). Taxonomy was assigned to ASVs using the q2-feature-classifier⁶⁰ classify-sklearn naïve Bayes taxonomy classifier against the Greengenes database (13_8, OTUs with 99% similarity). The QIIME pipeline was also used to compute α- and β-diversity using the Shannon Index and weighted and unweighted UniFrac distances based on the ASVs relative abundance. Functional profile was performed by Picrust2 based on ASVs abundance using q2-picrust2.

Unless otherwise stated, statistical analyses were performed using R software. The differential diversity and abundance of genera, or ASVs between AD patients and after AIT were tested using the paired Wilcoxon signed-rank test. Only genera, or ASVs that were present in at least 20% of samples from each body site were included in the test. The p-values were adjusted by the Benjamini-Hochberg correction for multiple tests when required. Permutational multivariate analysis of variance based on weighted and unweighted UniFrac distances was performed with 999 permutations in R (3.4.0, vegan package) to assess the impact of AD on the microbiota at baseline and 6 and 12 months. The correlation coefficients of repeated observations between genus were calculated using the method described by Bland and Altman.⁶¹ The relationships between microbial data and clinical parameters were assessed using Linear Mixed-Effects Models with the lmerTest package in R.

Antibiotic treatment to remove microbiota

In the mouse model of Calcipotriol (MC903; LEO Pharma)-induced AD, adult mice (6-week-old) were intragastrically administrated with antibiotics containing 200 μL of ampicillin (1 g/kg; MedChemExpress, USA) and streptomycin (2 g/L; MedChemExpress) daily for 3 days as previously described.⁶²^,⁶³ After the last dose of antibiotics, the mice were topically treated with MC903.

Fecal transplantation of microbiota

Mice were intragastrically administered with antibiotic cocktail (ABX) daily for 3 days as mentioned above, and then were topically treated with 2 nmol of MC903 for daily 12 days. Once the dermatitis was fully induced, 2 nmol of MC903 was applied every other day for 25 days to maintain the skin inflammation. At the same time, mice were gavaged with gut microbiota from patients with AD (AD group), healthy controls (HC group), and AD patients markedly improved by AIT (AIT group) daily for 15 days. Intragastrical phosphate buffered saline (PBS) was used as control (NC group). To prepare the gut microbiota for gavage, 5 samples from each group were randomly selected and mixed with equal amount. One gram of the mixed stool was then suspended in 10 mL PBS. The stool was mixed with vortex for 2 min to homogenate. Then, undigested food and small particulate matter was successively removed through 2.0, 1.0, 0.5, and 0.25 mm stainless steel screens. An aliquot of 200 μL suspension for each mouse was used for gavage.

Bacteria strains, isolation, and preparation

B. vesicularis strain (CGMCC, #1.3355) was purchased from CGMCC and cultured aerobically in sterilized chopped meat medium (Bowei Biotech, China) under aerobic conditions at 37°C. Cultures were collected by centrifugation at 4000 rpm for 10 min, resuspended in sterile PBS solution to 5 × 10⁹ colony-forming units (CFUs)/mL, and preserved in −80°C condition. For the isolation of Bacteroides uniformis, Ruminococcus gnavus, and Prevotella copri, human fecal samples were collected and resuspended in sterile cold PBS. The bacterial suspensions were spread onto Brain Heart Infusion broth containing 5% sheep blood agar or DSMZ 104 medium and incubated for 2 to 7 days under anaerobic conditions at 37°C. Bacterial DNA was extracted from each single colony and the identity of individual isolates was verified by Sanger sequencing of the V1-V9 regions of 16S rRNA genes.

Mouse model

Mice were intragastrically administered with ABX daily for 3 days and then were gavaged with 200 μL of B. vesicularis or B. uniformis (1 × 10⁹ CFU) daily for 7 days. Intragastrical PBS was used as control. Thereafter, gavage was continued while mice were topically treated with 1 nmol of MC903 and 25 μL of OVA (20 μg/μL; Sigma-Aldrich, USA) daily for 15 days to produce the AD mouse model. For AIT experiment, mice were intragastrically administered with ABX daily for 3 days, and then were gavaged with 200 μL of B. vesicularis (1 × 10⁹ CFU) daily for 7 days. Intragastrical PBS was used as control. Thereafter, gavage was continued while mice were topically treated with 1 nmol of MC903 and 25 μL of OVA (20 μg/μL) daily for 14 days to produce the AD mouse model. Once the dermatitis was fully induced, 2 nmol of MC903 was applied every other day for 5 days to maintain the skin inflammation. Starting on day 10 of dermatitis induction, mice were injected subcutaneously with 200 μL of OVA solution (100 μg OVA and 1 mg aluminum hydroxide dissolved in normal saline) once every 4 days for 3 consecutive times, using normal saline as a control. Fresh feces were collected in sterile plastic tubes using a clean technique at the time points indicated, then immediately stored at −80°C until used for 16S rRNA sequencing and quantitative real-time PCR analysis. At the end of the treatment, mice were euthanized using CO₂. Skin tissue was either fixed in formalin for histopathological analysis or stored at −80°C for mRNA expression detection. Blood samples were collected for ELISA. The CLNs, MLNs, and spleens were harvested for further flow cytometry analysis and cell culture.

Skin inflammation assessment and histopathology

At the time points indicated, full thickness of the ears was measured with dial calipers. The ear was cut into pieces, fixed in 4% formalin, and 6 μm sections were prepared and stained with hematoxylin and eosin (H&E) for evaluation of the ear thickness and inflammation. Slides were imaged using NanoZoomer digital pathology microscope (Hamamatsu Photonics, Hamamatsu City, Japan).

ELISA

For analysis of serum total IgE and OVA-specific IgE, 96-well microplate was precoated with 100 μL/well of purified rat ant-mouse IgE (1 μg/mL) overnight at 4°C, then blocked with 200 μL/well of 10% heat-inactivated fetal calf serum (FBS; Gibco, USA) at room temperature for 30 min, followed by incubation with diluted sera at room temperature for 2 h. Biotin-labeled rat anti-mouse IgE (2 μg/mL) and Biotin-labeled OVA (2.5 μg/mL) was added afterward. Then, after washing the plate was incubated with 100 μL/well of streptavidin-HRP. After incubation for 40 min at room temperature, tetramethylbenzidine (TMB, Beyotime, China) was added and the reaction was stopped by adding 50 μL/well of 2M H₂SO₄. The absorbance was measured at wavelength 450 nm. The levels of TGF-β1, IL-6, IL-17A, and IFN-γ in the supernatants were measured using the ELISA kits (Fcmacs Biotech, China) according to the manufacturer’s instructions.

Flow cytometry

Single-cell suspension (10⁶ cells/tube) was incubated with FcR Blocking Reagent (Miltenyi Biotec, Germany) to block Fc receptors for 15 min at 4°C. For surface staining, the cells were stained with antibodies or matched isotype control for 20 min at 4°C in the dark. The antibodies included anti-mouse CD3e-PECYN7, CD4-FITC, CD25-APC, CD86-APC, PD-L1-PECYN7 (eBioscience, USA), CD8-Percpcy5.5, CD11c-PE, MHCII-Alexa Flour 700, MHCII-pacific blue, PD-L1-brilliant violet 510 and CD103-FITC antibodies (Biolegend, USA). For intracellular staining, cells were cultured in the presence of 2 μL/mL cell stimulation cocktail (eBioscience) for 6 h. The cells were fixed and permeabilized using fixation and permeabilization solutions, then stained with anti-mouse Foxp3-PE, IL-4-APC, IFN-γ-PE antibodies (eBioscience), IFN-γ-Brilliant Violet 510, IL-17a-Brilliant Violet 605 (Biolegend), RORγt-Brilliant Violet 421 (BD Biosciences, USA) or isotype control for 30 min at 4°C in the dark. The cells were detected using BD FACSVerse (BD Biosciences) or Aurora (Cytek, Fremont, CA, USA), and data were analyzed using the FlowJo 10.0.7 software (Tree Star, Ashland, OR, USA). For flow cytometry analysis, cells in single live CD3⁺CD4⁺CD8⁻ cells gates were identified as Th cells, then Th1 cells were gated as IFN-γ⁺, Th2 cells were gated as IL-4⁺, Tregs were gated as CD25⁺Foxp3⁺, and Th17 cells were gated as RORγt⁺.⁶⁴

Quantitative real-time PCR (qRT-PCR)

Total DNA was extracted from 100 mg of fecal samples per mouse using a FastPure Host Removal and Microbiome DNA Isolation Kit (Vazyme, China). The relative abundance of total bacteria (16S rRNA) or B. vesicularis was determined by qRT-PCR. For other targeted gene expression analysis, total RNA was extracted from the ear skin using TRIzol (Invitrogen, Thermo Fisher Scientific, USA) according to standard protocol. Complementary DNA was prepared with HiScript II Q RT SuperMix, and qRT-PCR was carried out using AceQ qPCR SYBR Green Master Mix (Vazyme) according to the manufacturer’s instructions. Gene expression was analyzed by real-time PCR (LC-480, Roche). Each gene was normalized to β-actin and evaluated using the ΔΔCT method to calculate the fold change. The following primers were used for qRT-PCR:

16S rRNA forward primer 5′-AAGCGGTGGATGATGTGGAT-3’

16S rRNA reverse primer 5′-GCGTAGCAACTAAGGACAAGG-3’

B. vesicularis forward primer 5′-TTGCCTTTGATACTGGGTGTCTTG-3’

B. vesicularis reverse primer 5′-CTTCGCCACTGGTGTTCTTCC-3’

Tslp forward primer 5′-ACGGATGGGGCTAACTTACAA-3’

Tslp reverse primer 5′-AGTCCTCGATTTGCTCGAACT-3’

Il17a forward primer 5′-TCAGCGTGTCCAAACACTGAG-3’

Il17a reverse primer 5′-CGCCAAGGGAGTTAAAGACTT-3’

Il22 forward primer 5′-ATGAGTTTTTCCCTTATGGGGAC-3’

Il22 reverse primer 5′-GCTGGAAGTTGGACACCTCAA-3’

Rorγt forward primer 5′-GACCCACACCTCACAAATTGA-3’

Rorγt reverse primer 5′-AGTAGGCCACATTACACTGCT-3’

Il6 forward primer 5′-TAGTCCTTCCTACCCCAATTTCC-3’

Il6 reverse primer 5′-TTGGTCCTTAGCCACTCCTTC-3’

β-Actin forward primer 5′-GTGACGTTGACATCCGTAAAGA-3’

β- Actin reverse primer 5′-GCCGGACTCATCGTACTCC-3’

DC-T cell co-culture

MLNs and spleens were harvested and grinded with syringe pistons, and then were filtered through a 200-mesh strainer to get single-cell suspension for cell culture. For isolation of splenocytes, red blood cells were removed by RBC lysis buffer (Miltenyi Biotec). For experiments of CD4⁺ T cells and CD11c⁺ DCs co-culture, CD4⁺ T cells were sorted from splenocytes of wild-type BALB/c mice by CD4 (L3T4) MicroBeads (Miltenyi Biotec), and CD11c⁺ cells were sorted from MLNs or splenocytes of wild-type BALB/c mice by CD11c-PE antibody (eBioscience) and Anti-PE MicroBeads (Miltenyi Biotec). CD11c⁺ DCs (5 × 10⁵ cells/ml) were then washed and co-cultured with live or heat-killed B. vesicularis, or commensal bacterial strains (2.5 × 10⁷ CFU/mL), or LPS (1 μg/mL) for 24 h, in the presence of LPS (0.5 μg/mL; Sigma-Aldrich) in RPMI-1640 culture medium supplemented with 10% heat-inactivated FBS. For the analysis of pre-inflammatory cytokines, the supernatants were harvested and examined for TGF-β1 and IL-6 using ELISA. For DC-T cell co-culture, the pre-stimulated CD11c⁺ DCs (5 × 10⁵ cells/ml) were co-cultured with CD4⁺ naive T cells (2 × 10⁶ cells/ml) for 4 days, in the presence of IL-2 (10 ng/mL; R&D Systems, USA) in RPMI-1640 culture medium supplemented with 10% heat-inactivated FBS, 100 U/ml penicillin and 100 μg/mL streptomycin. Then the supernatants (from splenic DC-CD4⁺ T cell co-culture system) were harvested and examined for IL-17A and IFN-γ using ELISA, and the cells (from MLN DC-CD4⁺ T cell co-culture system) were analyzed for polarization of CD4⁺ Th cells analysis by flow cytometry.

Quantification and statistical analysis

Data are expressed as means ± SD or SEM. Statistical comparisons between 2 groups were analyzed with paired or unpaired two-tailed Student’s t test and multi-group data were performed with ANOVA using GraphPad Prism 9.0 (GraphPad Software Inc., San Diego, CA, USA). A p value <0.05 was considered statistically significant.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (82073446, 82103735, 81972939, 81803144, and 82273542), the National Key R&D Program of China (2022YFC3601800), the Key Project of Social Development in Jiangsu Province (BE2020632), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-059), Nanjing Incubation Program for National Clinical Research Center (2019060001), and the Key Project of the Innovation Program of Shanghai Municipal Education Commission (2021-01-07-00-07-E00078). The experiments were conducted in Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs.

Author contributions

X.Y. and W.L. designed the experiments, analyzed the data, and wrote the manuscript. S.X.L. coordinated the research and provided input on experimental design. X.L., B.X., X.X., and Z.W. performed the experiments, analyzed the data, and wrote the manuscript. Y.L., Y.G., S.L., A.W., Y.Z., and X.W. performed the experiments.

Declaration of interests

The authors declare no competing interests.

Published: December 19, 2023

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.xcrm.2023.101340.

Contributor Information

Sean Xiao Leng, Email: sleng1@jhu.edu.

Wei Li, Email: liweiderma@fudan.edu.cn.

Xu Yao, Email: dryao_xu@126.com.

Supplemental information

Document S1. Figures S1‒S7, Tables S1 and S2, and Data S1

mmc1.pdf^{(2.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(6.9MB, pdf)}

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Associated Data

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

Supplementary Materials

Document S1. Figures S1‒S7, Tables S1 and S2, and Data S1

mmc1.pdf^{(2.1MB, pdf)}

Document S2. Article plus supplemental information

mmc2.pdf^{(6.9MB, pdf)}

Data Availability Statement

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PERMALINK

Attenuation of allergen-specific immunotherapy for atopic dermatitis by ectopic colonization of Brevundimonas vesicularis in the intestine

Xiaochun Liu

Beilei Xu

Xiaoqiang Xu

Zhifeng Wang

Yang Luo

Yingxia Gao

Shiqi Ling

Ao Wang

Yuan Zhou

Xiaokai Wang

Sean Xiao Leng

Wei Li

Xu Yao

Summary

Graphical abstract

Highlights

Introduction

Results

The improvement in AD following AIT is accompanied by alterations in the oral and gut microbiota

Figure 1.

Transplantation of fecal microbiota from patients undergoing AIT improves AD-like dermatitis in mice

Figure 2.

Abundance of B. vesicularis in the oral and gut microbiota is decreased after AIT

Figure 3.

B. vesicularis from the oral cavity colonizes the gut of patients with AD

Figure 4.

B. vesicularis is associated with AD-related clinical parameters

Intragastric B. vesicularis aggravates MC903-induced AD-like dermatitis in mice

Figure 5.

B. vesicularis attenuates AIT efficacy in AD mice

Figure 6.

Discussion

Limitations of the study

STAR★Methods

Key resources table

Resource availability

Lead contact

Materials availability

Data and code availability

Experimental model and study participant details

Human studies

Animal studies

Method details

16S rRNA gene sequencing and analysis

DNA extraction and 16S rRNA sequencing

16S sequencing data analysis

Antibiotic treatment to remove microbiota

Fecal transplantation of microbiota

Bacteria strains, isolation, and preparation

Mouse model

Skin inflammation assessment and histopathology

ELISA

Flow cytometry

Quantitative real-time PCR (qRT-PCR)

DC-T cell co-culture

Quantification and statistical analysis

Acknowledgments

Author contributions

Declaration of interests

Footnotes

Contributor Information

Supplemental information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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