
==== Front
NPJ Biofilms Microbiomes
NPJ Biofilms Microbiomes
NPJ Biofilms and Microbiomes
2055-5008
Nature Publishing Group UK London

39266529
563
10.1038/s41522-024-00563-z
Article
Protection against DSS-induced colitis in mice through FcεRIα deficiency: the role of altered Lactobacillus
Yin Yue 1
Wang Ruilong 2
Li Yanning 1
Qin Wenfei 3
Pan Letian 4
Yan Chenyuan 4
Hu Yusen 4
Wang Guangqiang 3
Ai Lianzhong ailianzhong1@126.com

3
Mei Qixiang poise1236@126.com

45
Li Li annylish@126.com

1
1 grid.16821.3c 0000 0004 0368 8293 Department of Laboratory Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
2 grid.8547.e 0000 0001 0125 2443 Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, China
3 https://ror.org/00ay9v204 grid.267139.8 0000 0000 9188 055X School of Health Science and Engineering, Shanghai Engineering Research Center of Food Microbiology, University of Shanghai for Science and Technology, Shanghai, China
4 https://ror.org/0220qvk04 grid.16821.3c 0000 0004 0368 8293 Shanghai Key Laboratory of Pancreatic Disease, Shanghai JiaoTong University School of Medicine, Shanghai, China
5 grid.16821.3c 0000 0004 0368 8293 Department of Gastroenterology, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
12 9 2024
12 9 2024
2024
10 849 3 2024
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The role of mast cells (MCs) in ulcerative colitis (UC) development is controversial. FcεRI, the IgE high-affinity receptor, is known to activate MCs. However, its role in UC remains unclear. In our study, Anti-FcεRI showed highly diagnostic value for UC. FcεRIα knockout in mice ameliorated DSS-induced colitis in a gut microbiota-dependent manner. Increased Lactobacillus abundance in FcεRIα deficient mice showed strongly correlation with the remission of colitis. RNA sequencing indicated activation of the NLRP6 inflammasome pathway in FcεRIα knockout mice. Additionally, Lactobacillus plantarum supplementation protected against inflammatory injury and goblet cell loss, with activation of the NLRP6 inflammasome during colitis. Notably, this effect was absent when the strain is unable to produce lactic acid. In summary, colitis was mitigated in FcεRIα deficient mice, which may be attributed to the increased abundance of Lactobacillus. These findings contribute to a better understanding of the relationship between allergic reactions, microbiota, and colitis.

Subject terms

Clinical microbiology
Applied microbiology
National Key Research and Development Program of China (No. 2022YFC2009600), the Natural Science Foundation of China (No. 81871267).Natural Science Foundation of China (No. 82270671)National Natural Science Foundation--Youth Foundation (No.82200714), Xinyi Digestive Disease Research Fund (No. KY-2023-03-01).issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Inflammatory bowel diseases (IBD) are chronic disabling gastrointestinal disorders, comprising ulcerative colitis (UC) and Crohn’s disease (CD). Incidence of UC has been increasing in the Western world since the mid-twentieth century, with most new cases being diagnosed in adolescence and early adulthood1,2, the direct and indirect cost of UC is considerable3. Previous studies have suggested that basophil granulocytes and tissue mast cells (MCs), along with their mediators, contribute to the development of various immune and inflammatory disorders4–6, and some studies have also indicated that MCs may be involved in the occurrence and progression of UC7,8. The contribution of MCs to gut inflammation may occur through the regulation of permeability in the affected epithelium, as evidenced by studies using the DSS-induced colitis model9. However, the specific mechanism by which MC exacerbates DSS-induced colitis is not clear.

Fc epsilon RI (FcεRI) is a characteristic membrane receptor on the surface of MCs. Its immunoglobulin domain-containing α-chain could bind the Fc-part of IgE. Allergen-mediated crosslinking of IgE-FcεRI complexes on the surface of blood and tissue cells then triggers the allergic cascade10. Besides, α-chain is also a recognition fragment of anti-FcεRI autoantibodies, which directly bind to receptors to activate cells and participate in the development of autoimmune disease11. Although high levels of serum IgE have been observed in UC patients compared with health controls (HCs)12, the role of IgE and FcεRI in UC pathogenesis remains controversial. Imbalance in the gut microbial community has been identified as a crucial factor in the development of UC13–15. The products produced by gut flora or microorganisms can interact with various ligands and receptors on the surface of MCs, suggesting that the interplay between MCs and the microbiota metabolites may have a significant impact on the pathogenesis of UC16–18. Therefore, investigating the potential link between MCs and gut microbiota, particularly in relation to FcεRIα, may provide valuable insights into the impact of these factors on colitis.

This study aims to investigate the relationship between FcεRIα deficiency, gut microbiota, and DSS-induced colitis. Besides, a new biomarker is explored to provide updated evidence for the diagnosis of UC patients. Up to now, this is the first study exploring the association between allergic reactions and intestinal microbiota in UC, laying the foundation for further exploration of the relationship between various allergic reactions and intestinal microbiota.

Results

Anti-FcεRI is a potential diagnostic marker for ulcerative colitis

In the year 2020 to 2021, 62 UC patients (48 patients from Shanghai General Hospital and 14 patients from Shanghai Renji Hospital) and 75 health volunteers (HCs) were recruited to explore their serum IgE, anti-IgE (aIgE), and anti-FcεRI (aFcεRI) levels. As shown in Supplementary Table 1, there was no significant difference between the two groups in term of demographic indicators such as gender and age (P > 0.05).

FcεRI, a high-affinity receptor for IgE primarily found on mast cells (MCs) and basophils10, is crucial for MC activation, with the IgE-FcεRI interaction playing a pivotal role in this process11. In this study, we found heightened serum IgE level in UC patients compared with HCs (Fig. 1A). However, the level of aIgE did not exhibit significant differences between HCs and UC patients (Fig. 1B). Interestingly, levels of aFcεRI were significantly elevated in the serum of UC patients compared with HCs (Fig. 1B). In the year 2020–2021, a total of 48 UC patients from Shanghai General Hospital were included in the Training cohort. As shown in Fig. 1C and Supplementary Fig. 1A, It was found that aFcεRI exhibited a diagnostic value of 0.848 (95% CI 0.778–0.919) for forecasting UC, surpassing the IgE (0.614, 95% CI 0.513–0.715) and aIgE (0.591, 95% CI 0.485–0.698), even the standard clinical diagnostic markers GAB (0.583, 95% CI 0.477–0.690) and ANCA(0.820, 95% CI 0.734–0.906). Moreover, when combined with ANCA, aFcεRI achieved a diagnostic value of 0.956 (95% CI 0.921–0.990) (Fig. 1C). Interestingly, when combined with ANCA and GAB, the diagnostic value further increased to 0.963 (95% CI 0.932–0.995), surpassing any other combination (Supplementary Fig. 1A). Based on the observations above, 16 patients with UC enrolled in Shanghai Renji Hospital from 2020 to 2021 were selected as the validation cohort. As shown in Fig. 1D and Supplementary Fig. 1B, the results showed that aFcεRI exhibited a diagnostic value of 0.775 (95% CI 0.606–0.944), surpassing the IgE(0.603, 95% CI 0.438–0.768), aIgE (0.584, 95% CI 0.405–0.763), ANCA(0.880, 95% CI 0.749–1.000) and GAB(0.679, 95% CI 0.498–0.859). Combined diagnostic value of aFcεRI and ANCA reached 0.923 (95% CI 0.802–1.000) (Fig. 1D), and the combined diagnostic value of UC using aFcεRI, ANCA, and GAB yielded a value of 0.929 (95% CI 0.808–1.000), surpassing any other combination (Supplementary Fig. 1B).Fig. 1 aFcεRI is a potential diagnostic marker of ulcer colitis.

A Comparison of serum IgE level between healthy volunteers (HC, n = 75) and ulcer colitis (UC, n = 62) patients. B Comparison of serum Anti-IgE (left panel) and anti-FcεRI (right panel) level between HC and UC patients (HC, n = 75, UC, n = 62). C Diagnostic value of training cohort. D Diagnostic value of validation cohort. E Photomicrograph of Tryptase and FcεRI immunofluorescence in the colon from HC and UC patients (n = 6, separately) (200× magnification). F Numbers of Mast cells per HPF in the colon tissue of HC and UC patients (n = 6, separately). G mRNA expression of FcεRIα in the colon tissue of HC and UC patients (n = 6, separately). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; **: P < 0.01; ***: P < 0.001; ns means P > 0.05.

Microscopic analysis of colonic tissues from UC patients and HCs revealed a conspicuous increase in the expression levels of Tryptase (mast cell markers), FcεRI, and the number of MCs in UC patients compared with HCs (Fig. 1E, F). Furthermore, the mRNA expression of FcεRIα in UC patients significantly surpassed that in HCs (Fig. 1G). Collectively, these findings underscored anti-FcεRI as a promising diagnostic biomarker for UC.

FcεRIα ablation attenuate DSS-induced experimental colitis

Activation of MCs is critically influenced by FcεRI signaling, which is commonly associated with the binding of IgE to its α chain19. Based on the elevated serum levels of aFcεRI in UC, we established a murine model with FcεRIα knockout (FC) to simulate the role of FcεRIα in UC, with the experimental procedure detailed in Fig. 2A. As expected, the animals exhibited severe symptoms including shortened colon length after the DSS administration (Fig. 2B, C). To our surprise, FcεRIα mice with DSS treatment decelerated in disease progression, which was evident through improved colon length compared to wild-type (WT) mice (Fig. 2B, C).Fig. 2 FcεRIα knockout protected gut barrier and ameliorated the DSS-induced ulcer colitis in mice.

A Schematic illustration of DSS-induced colitis in mice with or without FcεRIα knockout. B The entire colon was harvested and photographed on day 10 and C colon length was analyzed (n = 8). D The body weight of the mice was measured and presented as a percentage of the original body weight (n = 8). E Disease activity index was calculated (n = 8). F Representative images of colon stained with hematoxylin (100× magnification), photomicrograph of Claudin1 immunofluorescence (100× magnification), colon mucus goblet cells stained with PAS (200× magnification), and the results of the statistical analysis are shown (right) (n = 8). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; **: P < 0 .01; ***: P < 0.001. CON: wild-type mice; FC: FcεRIα KO mice; DSS: DSS-induced colitis in WT mice; FCDSS: DSS-induced colitis in FC mice.

Furthermore, in comparison to WT mice, DSS-induced WT mice showed aggravated weight loss and disease activity index (DAI). Meanwhile, DSS-treated FC mice exhibited reduced weight loss and DAI compared to that of the DSS-treated WT mice (Fig. 2D, E). Histological examination demonstrated that mice afflicted with colitis experienced aggravated tissue damage, as evidenced by increased epithelial damage and higher histopathological scores (Fig. 2F). Moreover, the integrity of the intestinal barrier was ruined in the colitis-induced mice, as indicated by decreased protein expression of intestinal barrier (Claudin1), reduced regeneration of the crypt architecture, and diminished goblet cells (MUC2 stained) compared to the control group (Fig. 2F). These unfavorable outcomes were all significantly reversed in FCDSS mice (Fig. 2F). Additionally, in our measurements of the serum levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) and anti-inflammatory cytokines (IL-10), we observed that the levels of IL-1β, IL-6, TNF-α were significantly elevated in DSS-induced WT mice compared to that in WT mice. IL-1β, IL-6, TNF-α were notably decreased in DSS-induced FC mice compared with DSS-induced WT mice (Fig. 3A–C). Meanwhile, the level of IL-10 in FC mice was significantly higher than that in WT mice, and the difference between the two groups was more obvious after DSS treatment (Fig. 3D).Fig. 3 Silencing FcεRIα ameliorated systemic inflammation and regulated gut immunity in DSS-induced colitis.

A–D The serum level of IL-1β, IL-6, TNF-α, and IL-10 in murine colons was examined by ELISA kit (n = 8). E–G Frequencies of Th17 cells (CD4+IL17A+) in the mesenteric lymph node (MLN) and spleen (n = 8). H–J Frequencies of Treg cells (CD4+CD25+Foxp3+) in mesenteric lymph node (MLN) and spleen (n = 8). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; *: P < 0.05; **: P < 0.01; ***: P < 0.001; ns means P > 0 .05. CON: wild-type mice; FC: FcεRIαKO mice; DSS: DSS-induced colitis in WT mice; FCDSS: DSS-induced colitis in FC mice.

Furthermore, we evaluated the levels of inflammatory cells during the experiment. Previous studies have indicated that the disruption of the homeostatic balance between pro-inflammatory Th17 cells and anti-inflammatory Treg cells plays a pivotal role in UC development20,21. Our study revealed that Th17 cell level in the DSS-treated WT group was higher in the mouse mesenteric lymph node (MLN) and spleen in comparison to that in WT group, while in the DSS-treated FC group, the TH17 cell level was lower than that in the DSS-treated WT group (Fig. 3E–G). However, Treg cell level showed a completely reversed trend in the four groups of mesenteric lymph node (MLN) and spleen, which was higher in the DSS-induced FC mice compared to that in the DSS-induced WT mice (Fig. 3H–J). In conclusion, our data suggested that FcεRIα deficiency had significant protective effects in DSS-induced colitis mice, characterized by attenuated systemic inflammation, alleviated tissue damage, preservation of intestinal integrity and goblet numbers, and restoration of the Th17/Treg balance.

FcεRIα ablation ameliorate DSS-induced gut dysbiosis

Considering the disruption of intestinal microbiota as a prominent characteristic of UC and its correlation with various disease manifestations, we proceeded to explore the effects of reduced FcεRIα on the gut microbiota of colitic mice. Our observations revealed that, in comparison to the control group, the α-diversity, a measurement for evaluating the richness and diversity of the microbial community as evaluated by the Shannon index, significantly reduced in mice induced with DSS-induced colitis (Fig. 4A). Strikingly, the FcεRIα deficiency effectively restored α-diversity in wild-type mice with or without DSS treatment (Fig. 4A). As shown in Fig. 4B and Supplementary Table 2, Principal coordinate analysis (PCoA) and PERMOANOVA analysis unveiled a distinct shift in the composition of the gut microbial community. DSS intervention did change the microbiota composition of the mice (p values CON vs DSS = 0.005**, FC vs FCDSS = 0.003**). Notably, the microbiota composition in the FC mice was significantly different from that in WT mice with or without colitis (p values CON vs FC = 0.002**, DSS vs FCDSS = 0.020*). The results highlighted the influence of FcεRIα on modulating the microbial composition in mice with or without DSS treatment.Fig. 4 Gut microbiota comparison between WT and FC mice with or without colitis.

A Rarefaction measure of intestinal microbial population. B Principle coordination analysis (PCoA) based on gut microbiota. C The taxonomic composition distribution among four groups on phylum-level of fecal microbiota. D The taxonomic composition distribution among four groups on genus level of fecal microbiota. E Analysis of differences in the microbial taxa shown by LEfSe (LDA coupled with effect size measurements). F Wilcoxon rank-sum test bar plot showed the significant different microbiota on genus level in WT and FC mice with DSS treatment. G Relative abundance of Alistipes, norank_f_Lachnospiraceae, Lactobacillus, and Lachnospiraceae_NK4A136 were shown (genus level). Data are provided as the mean ± SEM (n = 6 per group). P values were determined by unpaired two-tailed Student’s t-test; *: P < 0.05. CON: wild-type mice; FC: FcεRIαKO mice; DSS: DSS-induced colitis in WT mice; FCDSS: DSS-induced colitis in FC mice.

To further investigate the implications of FcεRIα on the gut microbiota, a meticulous analysis was conducted at two distinct taxonomic levels- phylum and genus levels (Fig. 4C–G). As shown in Fig. 4C, D, substantial changes in the composition of gut microbiota at both the phylum and genus levels were observed in FC and WT mice, regardless of whether they were treated with DSS. To further investigate the specific changes in the gut microbiota, we analyzed differences in the gut microbiota at the genus level between the DSS-treated WT and FC groups (Fig. 4E, F). Bacteria at the genus level with high abundance and showing significant difference were illustrated in Fig. 4G. At the genus level, WT mice subjected to DSS treatment exhibited an elevated relative abundance of Alistipes compared to that of control group, whereas this trend was significantly attenuated upon FcεRIα knockout intervention (Fig. 4F, G). Concurrently, the norank_f_lachnospiraceae level was higher in the FCDSS group compared with that of the DSS group, while the FC and the control group showed no difference (Fig. 4G). However, in FcεRIα knockout mice, no significant difference was observed in Lachnospiraceae_NK4A136 level regardless of the 3% DSS treatment compared with the WT group (Fig. 4G). Remarkably, we surprisingly found that FcεRIα knockout mice regardless of the 3% DSS treatment both showed substantially higher levels of Lactobacillus than that in WT mice (Fig. 4E–G). These findings collectively suggested that FcεRIα intervention had a great impact on the diversity and structure of the gut microbiota, countering the perturbations induced by DSS and thwarting dysbiosis.

Fecal microbiota from FcεRIα deficiency mice transfers protection against colitis

To ascertain the vital role of the gut microbiome in FcεRIα signaling, we conducted a series of microbiota-transfer experiments. Firstly, we applied Fecal Microbiota Transplantation (FMT) methods. To validate the role of gut microbiota in FcεRIα deficiency effects in colitis, fecal microbiota from WT and FC mice were transplanted into antibiotic-treated WT mice and then induced colitis (Supplementary Fig. 2A). The recipient mice that received fecal material from WT mice (referred to as FMT1) exhibited several negative effects compared to the control group. These effects include a reduction in colon length, worsening of body weight changes, and an increase in histological and DAI scores (Supplementary Fig. 2B–E). Furthermore, the levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) increased, but no significant difference was observed in IL-10 between the FMT1 group and the control group (Supplementary Fig. 2F). Additionally, the FMT1 group displayed aggravated histological characteristics, decreased level of the tight junction protein Claudin1, and reduced number of goblet cells compared to the control group (Supplementary Fig. 2G). However, recipient mice with FC fecal material (referred to as FMT2) exhibited enhanced colon length, improved body weight dynamics, and decreased histologic and DAI scores compared with the FMT1 group (Supplementary Fig. 2B–E). The levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) were reduced, while anti-inflammatory cytokine IL-10 levels were increased in the FMT2 group compared with the FMT1 group (Supplementary Fig. 2F). In comparison with the FMT1 group, FMT2 group also showed improved histological features, presence of tight junction protein Claudin1, and number of goblet cells (Supplementary Fig. 2G). Therefore, we hypothesize that the therapeutic effects of FcεRIα deficiency on intestinal integrity, goblet cell numbers, and inflammatory response in colitis mainly depends upon its regulation of the gut microbiota.

Then, to further verify our hypothesis, cohousing methods were applied. The FcεRIα knockout mice were either individually housed or cohoused with WT mice for one month. Subsequently, they were subjected to one-week DSS administration and then euthanized on day 10 for the purpose of assessing clinical scores and disease manifestations (Fig. 5A). Consistent with findings in Fig. 2, the absence of FcεRIα significantly inhibited the progression of colitis in individually housed mice (Fig. 5B–F). When FcεRIα knockout mice and wild-type mice were housed together, the phenotypic differences between them became less noticeable. This similarity in phenotype was particularly evident in characteristics such as colon length, body weight, DAI scores, and histopathological scores (Fig. 5B–F). The group of WT mice cohabitating with FcεRIα knockout mice (co-WT) showed improved measurements compared to individually housed wild-type mice, while the same measurements in the FC mice cohousing with WT mice (co-FC) were worsened compared to individually housed FC mice (Fig. 5B–F).Fig. 5 Comparison of colonic inflammation in individually housed or cohoused mice.

A Schematic illustration of cohousing strategy. B The entire colon was harvested and photographed on day 10 and C Difference in colon length in four groups (n = 8). D Body weight and E disease activity index in four groups (n = 8). F Representative images of the colon stained with hematoxylin (100× magnification), photomicrograph of Claudin1 immunofluorescence (100× magnification), colon mucus goblet cells stained with PAS (200× magnification), and the results of the statistical analysis are shown (right) (n = 8). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; **: P < 0.01; ***: P < 0 .001; ns means P > 0.05. WT: wild-type mice treated with DSS; FC: FcεRIαKO mice treated with DSS; co-WT: WT mice treated with cohousing and received DSS treatment; co-FC: FC mice treated with cohousing and received DSS treatment.

We subsequently examined differences in intestinal integrity, goblet cell numbers, and immune responses between the cohoused mice and individually housed mice. Our results demonstrated that, unlike individually housed mice, co-WT and co-FC groups showed no significant discrepancies in colon pathological injury, intestinal tight junction protein (Claudin1) expression or the number of goblet cells (Fig. 5F). Additionally, as shown in Fig. 6A–D, the differences in pro-inflammatory (IL-1β, IL-6 and TNF-α) and anti-inflammatory cytokines (IL-10) between DSS-treated WT and FC individually housed mice disappeared after 30 days of cohousing.Fig. 6 The pro- and anti-inflammatory cytokine/cell levels in mice with and without cohousing.

A–D The serum level of IL-1β, IL-6, TNF-α, and IL-10 among four groups (n = 8). E–G Frequencies of Th17 cells (CD4+IL17A+) in the mesenteric lymph node (MLN) and spleen (n = 8). H–J Frequencies of Treg cells (CD4+CD25+Foxp3+) in mesenteric lymph node (MLN) and spleen (n = 8). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; **: P < 0.01; ***: P < 0.001; ns means P > 0.05. WT: wild-type mice treated with DSS; FC: FcεRIαKO mice treated with DSS; co-WT: WT mice treated with cohousing and received DSS treatment；co-FC: FC mice treated with cohousing and received DSS treatment.

In line with these findings, we found that the percentage of Th17 cells was suppressed in co-WT mice in comparison with DSS-induced WT mice (Fig. 6E–G), while the percentage of Treg cells increased (Fig. 6H–J) in the mesenteric lymph nodes (MLNs) and spleen (SP) of co-WT mice. Consistently, compared with DSS-induced FC mice, co-FC mice exhibited higher percentage of Th17 cells and lower percentage of Treg cells (Fig. 6E–J). Collectively, these data suggested that cohousing regulated immune-regulatory and intestinal barrier protective effects.

Subsequently, we embarked on an inquiry into the repercussions of cohousing on the composition of the intestinal microbiota. In consonance with the aforementioned observations, it was discerned that the Shannon alpha-diversity metric in the cohort of co-WT became highly consistent with that of the co-FC (Fig. 7A). As shown in Fig. 7B and Supplementary Table 3, PCoA and PERMOANOVA analysis unveiled a proximate alignment between the gut microbial configurations of co-WT and co-FC mice(p values co-WT vs co-FC = 0.228), standing in stark contrast to the distinctive microbial arrangement observed in individually housed colitic WT and FC mice(p values WT vs FC = 0.020*). A more intricate taxonomic analysis at two distinct hierarchical levels was subsequently undertaken to assess the gut microbiota (Fig. 7C, D). The outcomes underscored a semblance in microbiota structures between co-WT and co-FC mice at the phylum and genus levels. The differences in levels of Alistipes, norank_f_lachnospiraceae, Lactobacillus between individually housed WT and FC colitic mice disappeared after 30 days of cohousing (Fig. 7E).Fig. 7 Comparison of gut microbiota composition with and without cohousing.

A Rarefaction measure of intestinal microbial population. B Principal coordination analysis (PCoA) based on gut microbiota. C The taxonomic composition distribution among four groups on phylum-level of fecal microbiota. D The taxonomic composition distribution among four groups on genus level of fecal microbiota. E Relative abundance of Alistipes, norank_f_Lachnospiraceae, Lactobacillus, and Lachnospiraceae_NK4A136 were shown (genus level). F Spearman correlation analysis between abundance of different bacteria and histopathological score, goblet cells, and serum cytokines levels(IL-1β, TNF-α, IL-6, and IL-10). Data are provided as the mean ± SEM (n = 6 per group). P values were determined by unpaired two-tailed Student’s t-test; *: P < 0.05; ns means P > 0.05. WT: wild-type mice treated with DSS; FC: FcεRIαKO mice treated with DSS; co-WT: WT mice treated with cohousing and received DSS treatment; co-FC: FC mice treated with cohousing and received DSS treatment.

To further identify key bacteria that play an important role in this process, we selected the known inflammatory indicators (IL-6, TNF-α, IL-1β, IL-10) which reflect the severity of colitis and the number of goblet cells that represent the integrity of the mucus barrier and excluded collinearity using VIF analysis (Supplementary Table 4). It was then analyzed for association with the bacteria screened above. Notably, as shown in Fig. 7F, Spearman correlation analysis revealed the histopathological score of colons, the serum levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) were strongly negatively correlated with the relative abundance of Lactobacillus. And goblet cells, anti-inflammatory cytokines (IL-10) were strongly positively correlated with the abundance of Lactobacillus. However, there is no strong correlation between these indicators of colitic inflammation and other bacteria like Alistipes, norank_f_lachnospiraceae, and Lachnospiraceae_NK4A136. Collectively, the abundance of Lactobacillus was strongly related to the inflammatory response of colitis and goblet cell numbers in FcεRIα deficient DSS-induced colitis.

FcεRIα is a specific receptor that regulates mast cell activation. We thought that the decrease in the abundance of Lactobacillus may be due to the bacteriostatic action of mast cells. The bacteriostasis experiment found that the supernatant of activated mast cell significantly inhibited the growth of Lactobacillus compared with the control group (Supplementary Fig 3A). To further verify this result, we co-cultured activated MCs supernatant with Lactobacillus-rich bacterial suspensions. We found that the concentration of Lactobacillus decreased significantly with the increase of the concentration of activated Mast cell supernatant (Supplementary Fig 3B).

To summarize, FcεRIα knockout effectively changed the composition of the gut microbiota, marked by an elevation in the abundance of Lactobacillus. Lactobacillus may play a vital role in the protective effects of FcεRIα knockout against DSS-induced colitis.

NLRP6 inflammasome activation enriched in FcεRIα deficient mice can be activated by Lactobacillus

RNA sequencing of gut identified 295 differentially expressed genes (150 up, 148 down) between WT and FC mice in DSS-induced colitis (Fig. 8A). Interestingly, the KEGG pathway analysis suggested that genes affected by FcεRIα deficiency were mainly related to the NOD-like receptor (NLR) pathway (Fig. 8B). Interestingly, deeper investigation of altered NLR pathway found high enrichment for genes encoding components of the NLRP6 inflammasome between two groups (Fig. 8C). Previous studies have reported that NLRP6 can protect colitis by activating MUC2 or antimicrobial peptides (AMPs) secretion22,23. The genes associated with NLRP6 inflammasome (NLRP6, ASC, Caspase1, and IL-18), goblet cells (MUC2), and AMPs (Ang4, ITLN1, RELMB) expression were found significantly elevated in FC colitic mice (Fig. 8D–F). The results suggested that the activation of NLRP6 inflammasome and its downstream products MUC2 and AMPs might be involved in the regulation of colitis through FcεRIα deficiency.Fig. 8 The genes related to NLRP6 inflammasomes were changed after FcεRIα deletion.

A The Volcano Plot illustrated the differentially expressed genes of the gut between two groups. B KEGG pathway analysis showed signaling pathways altered in two groups. C The heatmap of genes encoding components of the NLRP6 inflammasomes, chemokines, and goblet cells. D–F mRNA expression of NLRP6, ASC, Caspase1, IL-18 (D), MUC2 (E), Ang4, ITLN1 and RELMB (F) in mice gut. Data are provided as the mean ± SEM (n = 3 per group). P values were determined by unpaired two-tailed Student’s t-test; *: P < 0.05; **: P < 0.01; ***: P < 0.001. WT: wild-type mice treated with DSS; FC: FcεRIαKO mice treated with DSS.

Whereas the above studies indicated that FcεRIα deficiency affect colitis in a microbiota-dependent manner and that Lactobacillus may play a central role in this process. To further uncover the role of Lactobacillus in FcεRIα, in vitro and in vivo experiments were applied to investigate the association of the activation of NLRP6 inflammasome with Lactobacillus. As shown in Supplementary Fig. 4, L. plantarum (AR113) triggered the expression of genes in NLRP6 inflammasome pathway(NLRP6, ASC, Caspase1, and IL-18), goblet cells(MUC2) and AMPs (Ang4, ITLN1, RELMB) in TNF-α treated colonoids and DSS-treated Mice. Furthermore, Fecal microbiota from FcεRIα deficient mice also triggered the expression of these genes.

Collectively, the results suggested that NLRP6 inflammasome plays an important role in the regulation of FcεRIα deficient colitis and can be activated by Lactobacillus treatment.

Ameliorating DSS-induced colitis with lactate produced by Lactobacillus

Given the significant changes in Lactobacillus levels observed in previous sections, we proceeded to investigate whether Lactobacillus influences colitis and its underlying mechanism. Lactobacillus is a pivotal bacterium engaged in the synthesis of lactic acid (LA), thus we aimed to understand whether lactate played a pivotal role in colitis. We also determined whether LA treatment affected FcεRI expression or not, rat mast cell line RBL-2H3 were stained for surface FcεRIα and analyzed via flow cytometry. As shown in Supplementary Fig. 5A, B, LA did not affect FcεRI surface expression. The results suggested that FcεRI knockout was the initial factor, which affected intestinal homeostasis through a microbiota-metabolite dependent way to regulate colitis, was not affected by terminal metabolites like LA.

To gain deeper insights into the contribution of Lactobacillus in ameliorating inflammatory colitis, we devised an experimental setup to juxtapose the effects of L. plantarum (AR113) with those of a lactate dehydrogenase (LDH)-deficient variant of AR113, termed AR113 Δ1778Δ0467 (AR113Δ) (Fig. 9A). Subsequently, two cohorts of WT mice were subjected to a dietary regimen involving either AR113 or AR113Δ administration for seven days, after which they were subjected to experimental colitis induction via 3% DSS administration (Fig. 9B). The findings from this study demonstrated that mice receiving AR113 treatment exhibited mitigated systemic inflammation, alleviated tissue damage, preservation of goblet cells in DSS-induced colitis (Fig. 9C–H). In contrast, mice receiving AR113Δ treatment, which lacked the ability to produce lactic acid, did not show similar beneficial effects. This was supported by observations of colon length, body weight dynamics, and DAI measurements, while mice receiving AR113Δ treatment displayed exacerbated disease severity compared to those treated with AR113 (Fig. 9C–F). In addition, mice subjected to AR113Δ treatment showed increased expression of IL-1β, IL-6, TNF-α, in contrast to the lower levels observed in mice treated with AR113 (Fig. 9G). However, in terms of IL-10, there was no significant difference between the two bacteria-treated mice. Furthermore, higher histopathological scoring of colonic tissue, exacerbated gur barrier damage, and less goblet cells were revealed in mice subjected to AR113Δ treatment compared to mice treated with AR113 (Fig. 9H). Based on these collective observations, we postulated that Lactobacillus played an important role in mitigating symptoms associated with DSS-induced colitis primarily through the secretion of lactate acid.Fig. 9 Lactate produced by Lactobacillus plantarum ameliorated DSS-induced experimental colitis.

A Lactate levels in AR113 and AR113 Δ1778Δ0467 (LDH deficient). B Schematic illustration of Experimental design. C The entire colon was harvested and photographed on day 10 and D colon length was analyzed (n = 8). E The body weight of the mice was measured and presented as a percentage of the original body weight (n = 8). F Disease activity index was calculated (n = 8). G The serum levels of IL-1β, IL-6, TNF-α, and IL-10 in mice serum were examined by ELISA (n = 8). H Representative images of colon stained with hematoxylin (100× magnification), photomicrograph of Claudin1 immunofluorescence (100×magnification), colon mucus goblet cells stained with PAS (400× magnification), and the results of the statistical analysis are shown (right) (n = 8). Data are provided as the mean ± SEM. P values were determined by unpaired two-tailed Student’s t-test; *: P < 0.05; **: P < 0.01; ***: P < 0 .001. CON: wild-type mice without DSS treatment; DSS: DSS-induced colitis in WT mice; DSS + AR: DSS-induced colitis in mice with AR113 treatment; DSS + ARΔ: DSS-induced colitis in mice with AR113 Δ1778Δ0467 treatment.

Discussion

The role of mast cells and allergic action in the development of UC remains controversial. Although high levels of serum IgE have been observed in UC patients compared with HCs12,24, there are also studies showing that there is no significant difference in IgE level between UC patients and HCs25,26. Our clinical trials have revealed that UC patients exhibit elevated mast cells, IgE, and aFcεRI levels compared to the healthy control group, and demographic indicators such as gender and age make no significant difference (P > 0.05). Clinical study revealed that antibodies against FcεRI exhibited a high diagnostic value for forecasting UC. Moreover, we observed DSS-induced colitis was less severe in the mice lacking FcεRIα with DSS treatment. The gut microbiota analysis showed that the microbiota composition was significantly altered in FcεRIα deficient(FC) mice, especially the abundance of Lactobacillus. In addition, the strategies including cohousing and FMT confirmed that the gut microbiota plays a critical role in improving DSS-induced colitis in FC mice. Correlation analysis showed that the increase abundance of Lactobacillus in FC mice was strongly associated with reduced intestinal inflammation and increased goblet cell numbers. RNA sequencing suggested that the NLRP6 inflammasome pathway was activated in FC mice. However, the protective effect of Lactobacillus plantarum strains against colitis was not observed in its modified strains that did not produce lactic acid, indicating the existence of a relationship between bacteria, bacterial metabolites, and the FcεRIα signaling in colitis.

UC is an autoimmune disease accompanied with allergic reactions, typically presented with elevated MCs level and MC activation in UC patients27,28. Mast cell activation is crucial in allergic reactions29. However, the exact mechanism of allergic reactions and mast cells in UC is not clear yet. FcεRI is a high-affinity IgE receptor, predominantly expressed in MCs and basophils10. When IgE binds to the IgE receptor FcεRI, even a few antigens are sufficient to induce the MCs degranulation and activate signaling pathway30,31, and the α chain of FcεRI is commonly correlated with the combination of IgE32. Studies have revealed that in some autoimmune diseases, such as systemic lupus erythematosus, elevated IgE and FcεRI levels can trigger interferon responses that exacerbate self-destructive autoimmune responses, which correlate with disease severity4,33. Consistent with the previous study27,28, we have detected elevated MCs in UC patients compared with HCs. Moreover, elevated serum IgE level and increased expression of aFcεRI (the antibody of FcεRI) were also detected in the UC patients compared with HCs (Fig. 1), which indicates that allergic reactions were correlated with UC. Further training cohort and validation cohort found that aFcεRI exhibited a relative high accuracy for forecasting UC, surpassing the clinical diagnostic markers ANCA and GAB (Fig. 1), which indicated that FcεRI as the mast cell activation signal, is a potential diagnostic marker for UC.

Based on the results of clinical studies, it is speculated that FcεRI is strongly correlated with UC. The α-subunit of FcεRI is its binding region to IgE and is also a recognition fragment of anti-FcεRI autoantibodies19. We knockout FcεRIα to validate whether FcεRIα modulates the symptoms of UC. UC pathogenesis mainly depends on the gut barrier and gut immunity against inflammation34. The gut mucosal immune system, which encompasses lymph nodes, lamina propria, and epithelial cells, acts as a protective barrier to maintain intestinal tract integrity35. In this context, epithelial cells safeguard the physical health of the intestinal tract. They collaborate with immune and stromal cells to combat pathogens and prevent direct contact between pathogens and the epithelium36. Goblet cells, which are integral to the intestinal barrier, play a vital role in the maintenance of intestinal homeostasis and undergo notable alterations in cases of colitis37. In line with prior research, our study observed that compared with control group, mice with DSS-induced colitis exhibited heightened intestinal damage, characterized by disrupted intestinal barrier function, diminished goblet cell population, heightened systemic inflammation, and an imbalance in Th17/Treg ratios. Moreover, in our study, we demonstrated that FcεRIα knockout ameliorated the DSS-induced ulcer colitis, through protecting the gut barrier and regulating gut immunity (Figs. 2–3), but its underlying mechanism is not clear.

The human gut harbors 100 trillion different microbial organisms, including bacteria, viruses, fungi, and protozoa, which constitute the microbiota38. Previous studies have shown that alterations in the gut microbiota play a critical role in the pathogenesis of UC39–42, while the exact role of dysbiosis is still unclear43,44. Consistently, our study also verified altered gut microbiota in mice with colitis. The taxonomic composition distribution of fecal microbiota on phylum and genus level were significantly changed in mice with DSS-induced colitis compared to control group (Fig. 4). Additionally, the taxonomic composition distribution of fecal microbiota in FC mice and WT mice was much different, suggesting gut microbiota might play a role in the function of FcεRIα knockout in UC.

Gut microbiota is vital in the development of autoimmune and allergic diseases, which has been extensively studied in relation to UC and MCs45–49. Recent literature has reported numerous findings linking MCs to UC, highlighting the importance of investigating their interaction with the gut microbiota16,46. MCs modulate the mutual influence between the host and its microbiota through changes in their activation state16. In this study, we found that FC mice not only effectively alleviated intestinal inflammation, but also significantly altered the composition of intestinal microbiota, including several key species such as Lactobacillus, Alistipes, norank_f_lachnospiraceae and Lachnospiraceae_NK4A136. Given the important role of microbiota in ulcerative colitis, these results prompted our speculation that there is a close correlation between the reduced inflammation in FC mice and the altered intestinal microbiota.

Studies attempting to determine whether dysbiosis is truly causative or merely a consequence of inflammation have suffered from a number of limitations, making it challenging to draw definitive conclusions. Fecal microbiota transplantation (FMT) is a commonly used experimental method to investigate the relationship between gut microbiota and diseases50. We comprehensively evaluate the role of gut microbiota in FcεRIα knockout functioning through FMT (Supplementary Fig. 2). Consistently, our experiments investigated that the influence of fecal microbiota transplanted from knockout mice could be inherited and attenuated disease phenotypes, confirmed the role of gut microbiota in FC mice.

Lactobacillus are Gram-positive rod-shaped microorganisms characterized by their ability to metabolize carbohydrate substrates into lactic acid through the process of lactic acid fermentation. Lactobacillus have been extensively investigated due to their probiotic effects on gastrointestinal microbiota51. The association between Lactobacillus and colitis suggests its potential involvement through diverse mechanisms, including reinforcement of the intestinal mucosal barrier, modulation of immune responses, and attenuation of inflammatory reactions45,52. The application of Lactobacillus in the research and treatment of colitis has gained significant attention53–55, offering potential avenues for developing novel therapeutic strategies. In this study, we detected a significant increase in the abundance of Lactobacillus in FC mice, and it was one of the most distinct bacteria between the FC and WT mice (Fig. 4E–G). Further cohousing experiments demonstrated that fecal microbiota from FC mice to WT mice transfers protection against colitis, which may be attributed to the assimilation of a variety of bacteria, including Lactobacillus, Alistipes, norank_f_lachnospiraceae and Lachnospiraceae_NK4A136 (Figs. 5–7). Additionally, by using correlation analysis, we found that Lactobacillus may be more likely to explain the remission of colitis in FC mice than other top-ranked differential bacteria (Fig. 7). In view of the cohousing treatment only delivered partial protection effect against colitis in WT mice, unassimilated species may have an equally strong protective effect. For example, Desulfovibrio, Odoribacter, Eubacterium_xylanophilum_group, and Enterorhadus showed increased abundance in WT mice after cohousing, coinciding with the amelioration of colitis. However, Desulfovibrio56, Enterorhadus57, and Eubacterium_xylanophilum_group58 have been reported associated with the worsening of colitis. Although Odoribacter has been reported the potential beneficial effects against colitis59, there is no significant differences in abundance between FC and WT mice, and its abundance did not decrease correspondingly with the worsening colitis in FC mice after cohousing. These results suggest that Lactobacillus, rather than these less abundant and non-assimilated bacteria, is significantly associated with the remission colitis in FcεRIα knockout mice.

It has been reported that mast cells can degranulate and release ROS, TNF-α, and PGD2 to exert anti-bacterial effects60. Consistently, we co-cultured activated MC supernatants with Lactobacillus suspensions, and found that the concentration of Lactobacillus decreased significantly with the increase of the concentration of activated Mast cell supernatant (Supplementary Fig. 3). FcεRIα is a specific receptor that regulates mast cell activation19. Our finding indicated that the abundance of Lactobacillus might be affected by mast cell activation, which may explain the increased Lactobacillus levels in FcεRIα knockout mice. However, the in vitro experiments have certain limitations, it can not reflect the real situation in vivo. Given that in vivo microbiota are affected by multiple factors, this conjecture still needs further study.

NOD-like receptors (NLRs), consisting of NOD1, NOD2, NLRP3, NLRP6, etc., serve as pattern recognition receptors involved in various innate immune responses61–63. Previous studies have demonstrated that NLRs participated in the pathogenesis of various diseases, including UC64,65. Consistently, our study identified that compared to WT mice, the NLR signaling pathway was enriched in the FcεRIα knockout mice through transcriptome sequencing, among which the NLRP6 pathway was significantly enriched and up-regulated. NLRP6 belongs to the NLR family66, which is reported to be involved in inflammasome activation, mucus secretion, and antimicrobial peptides (AMPs) production23, and is vital for the protection of the gut barrier. The NLRP6 inflammasome plays a crucial role in orchestrating goblet cell mucin granule exocytosis67. Mucus, produced by goblet cells in the large intestine, acts as an essential antimicrobial mechanism in the mammalian intestinal ecosystem67. Previous studies have reported that NLRP6 inflammatosomes may improve colitis by activating AMPs (Ang4, ITLN1, RELMB)22. Our findings demonstrated an increase in the abundance of goblet cells and AMPs (Ang4, ITLN1, RELMB) in FcεRIα knockout mice. These results strongly implied that the alleviated colitis symptoms in FcεRIα knockout mice might be attributed, at least partially, to the activation of intestinal NLRP6 and subsequent preservation of goblet cells and activation of AMPs.

We subsequently endeavored to explore the specific mechanism of how the Lactobacillus modulates colitis. Lactobacillus is a pivotal bacterium engaged in the synthesis of lactic acid, which can inhibit pathogens and prevent cell apoptosis68,69. Previous studies have demonstrated that Lactobacillus participated in the pathogenesis of colitis45,54. Increased Lactobacillus level has therapeutic efficacy in colitis, by regulating immune responses and altering the composition of gut microbiota and its related metabolism45. Our study utilized L. plantarum to investigate the protective effect of Lactobacillus against colitis. In line with previous findings, our results revealed that supplementation with L. plantarum effectively ameliorated colonic injury in mice by reducing inflammation and promoting goblet cell proliferation (Fig. 9). Furthermore, our experiments demonstrated that L. plantarum supplementation activated the NLRP6 pathway both in TNF-α treated colonoids and DSS-treated Mice (Supplementary Fig. 4). Fecal microbiota from FcεRIα deficient mice triggered NLRP6 inflammasome in mice of colitis (Supplementary Fig. 4), further indicated that Lactobacillus, as a key species in fecal microbiota of FcεRIα deficient mice, may play a protective role in colitis by targeting NLRP6 inflammasome pathway. Collectively, these results suggested that in FcεRIα deficient mice, Lactobacillus protected mice from colitis-associated gut injury through mucus and AMPs secretion in a NLRP6 dependent manner.

Genetically engineered bacteria have been widely used to combat various diseases, which have unique properties such as enhanced targeting, versatility, self-amplification capabilities, and biodegradability70,71. It is suggested that gut microbiota-derived metabolites play a vital role in intestinal homeostasis during the pathogenesis of diseases72. Lactate is the main product of Lactobacillus73. Previous studies have demonstrated that lactate can relieve the symptoms of colitis74–76. To explore the potential significance of lactate in the beneficial effects of Lactobacillus on colitis, we employed genetic engineering techniques to generate lactate-deficient strains of Lactobacillus. Standard Lactobacillus (AR113) and Lactobacillus without the key enzyme of lactate synthesis (AR113Δ) were used to analyze the effects of lactate (Fig. 9). The findings demonstrated that mice receiving AR113 treatment exhibited ameliorated symptoms in DSS-induced colitis (Fig. 9). However, this anti-inflammatory effect was lost in Lactobacillus that could not synthesize lactic acid, indicated that Lactobacillus played a substantial role in alleviating symptoms linked to DSS-induced colitis, primarily through the secretion of lactate.

In conclusion, this study provides compelling evidence supporting the role of anti-FcεRI as the diagnostic marker for ulcerative colitis. The findings suggest that FcεRIα deficiency leads to a reduction in colonic inflammation possibly through alterations in gut microbiota - especially the increased abundance of Lactobacillus. The mechanisms through which Lactobacillus ameliorates colonic inflammation may be attributed to the activation of NLRP6 inflammasome and secretion of lactate acid. These findings contribute to a better understanding of the relationship between allergic reactions, intestinal microbiota, and the development of colitis, highlighting the potential of therapeutic interventions targeting mast cell-associated signaling pathways in UC. The experimental process and proposed mechanisms are summarized in the Graph Abstract in our supplemental information.

Methods

Participants experimentation and ethics

The clinical trial was conducted between May 2020 and August 2021. All the participants enrolled were 18 years of age or older and provided their signed informed consent, and demographic indicators such as gender and age make no significant difference (P > 0.05). The ethics committee of Shanghai General Hospital approved the protocols (2020SQ097) and the study was registered with ClinicalTrials.gov (NCT02435160). A total of 62 UC patients (48 patients from Shanghai General Hospital and 14 patients from Shanghai Renji Hospital) were selected from the Department of Gastroenterology. Additionally, 75 healthy controls (HCs) were recruited. All eligible UC participants had an established diagnosis of UC. Potentially eligible UC participants were scheduled for a colonoscopy and baseline questionnaires to obtain the total and endoscopic Mayo scores. The patients with a total Mayo score of ≥4 points and an endoscopic subscore of ≥2 were considered eligible. Patients were excluded if they had a severe disease that was defined by a total Mayo score of 11–12 or if the physician’s rating of disease activity was >2. Patients with biological agents were excluded from the study. Blood samples from the participants were tested for allergic-related markers (IgE and FcεRI). Tissue samples were collected from participants to examine the number of mast cells and the FcεRI expression. Other exclusion criteria were severe disease that required hospitalization, pregnancy, or use of antibiotics or probiotics within 30 days.

Receiver operating characteristic

Receiver operating characteristic (ROC) analysis was conducted by plotting the true positive rate against the false positive rate for different thresholds as previous described77. The area under the curve (AUC) was calculated to measure the performance of the diagnostic test.

Animal experiments

Six to eight weeks old female BALB/c mice were purchased from the Shanghai Model Organisms Center. FcεRIα knockout (FC) mice were constructed by Beijing Viewsolid Biotech Co.LTD, commissioned by our research group. All the mice were kept under pathogen-free and housing conditions in a 12 h light/dark cycle. All the animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of Shanghai General Hospital (2020AW095) and conducted according to the instructions of the IACUC. Colitis was induced by the administration of 3% DSS (molecular mass 36–50 kDa, 9011-18-1, sigma, MP Biomedicals, USA) through drinking water. In the first part of our animal experiments, mice treatment was illustrated in Fig. 2A. The mice were randomized and divided into the following groups (n ≥ 6 for each group): ①Wild-type mice with drinking water (abbreviated as CON), ②FcεRIα knockout mice with drinking water (abbreviated as FC), ③WT mice with 3% DSS (abbreviated as DSS), and ④FcεRIα knockout mice with 3% DSS (abbreviated as FCDSS).

In the cohousing experiment depicted in Fig. 5A, groups of WT and FC mice were either cohoused for 30 d (abbreviated as co-WT, co-FC, respectively), or were separately housed (abbreviated as WT, FC, respectively), and then the four groups of mice received 3% DSS administration. Fecal microbiota transplantation (FMT) treatments are illustrated in Supplementary Fig. 2A. In our FMT experiment, three groups of mice are included in the FMT experiment, one group of mice receiving saline served as a control group (abbreviated as CON). Two groups of WT mice were treated with antibiotic cocktail for 2 weeks to generate enteric germ-free mice. Feces from WT mice and FC mice were transplanted to them separately (abbreviated as FMT1 and FMT2, respectively) and then received 3% DSS administration to induce colitis.

The flow chart of the Lactobacillus intervention is in Fig. 9B. Four groups of mice are included in the Lactobacillus intervention experiment, one group of mice receiving saline served as the control group (abbreviated as CON), another group of mice treated with 3% DSS (abbreviated as DSS). Besides, AR113 and AR113 Δ1778Δ0467 were gavaged into two groups of WT mice for 7 d respectively and then treated with 3% DSS (abbreviated as DSS + AR, DSS + ARΔ, respectively).

The disease activity index (DAI), weight measurement, and entire colon length were measured as previously described by Zhenhua et al.49. In brief, the following parameters were used for DAI calculation: diarrhea (0 points, normal; 2 points, loose stools; 4 points, watery diarrhea) and hematochezia (0 points, no bleeding; 2 points, slight bleeding; 4 points, gross bleeding). Body weight, stool consistency, and the presence of gross blood in feces and at the anus were monitored every day. At 10 d, the mice were euthanized, and the entire colon length was measured.

Fecal DNA extraction and microbiome analysis

Initially, mice feces were collected in a sterile tube and then homogenized using a high-throughput grinder (Onebio. Biotech, CN). The homogenized feces were plated onto brain heart infusion agar (BHIA) plates for the cultivation of anaerobic bacteria. The plates were subsequently incubated at 37 °C under anaerobic conditions. After a 72-h incubation period, the colony-forming units (CFUs) were counted.

To identify bacterial DNAs in the mice feces, approximately 200 mg of feces were subjected to DNA isolation using the E.Z.N.A. Stool DNA Kit (Omega, USA), following the manufacturer’s instructions. The concentration of the extracted DNAs was determined using the NanoDrop2000 (Thermo Scientific, USA). For real-time PCR analysis, the QuantStudio 6 Flex Real-time PCR Systems (Thermo Scientific, USA) were used, along with universal primers targeting the bacterial 16S ribosomal RNA gene (Eub forward 5′-ACTCCTACGGGAGGCAGCAG-3′, reverse 5′-ATTACCGCGGCTGCTGG-3′). The fecal bacterial DNA levels were normalized to the host 18S rRNA (forward 5′-CTGAGAAACGGCTACCACATC-3′, reverse 5′-GCCTCGAAAGAGTCCTGTATTG-3′) in the mice samples.

Then we displayed High‐throughput sequencing and analysis by using Majorbio cloud(Shanghai, China) (https://cloud.majorbio.com). The resulting sequences were quality-filtered with fastp (0.19.6) and merged with FLASH (v1.2.11). Next, the high-quality sequences were denoised using the DADA2 plug-in in the QIIME2 (version 2020.2) pipeline with recommended parameters, which are called amplicon sequence variants(ASVs). Taxonomic assignment of ASVs was performed using the naive Bayes consensus taxonomy classifier implemented in QIIME2 and the SILVA 16S rRNA database (v138). Alpha-diversity indices(the Shannon index) was calculated with Mothurv1.30.1. Principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarity using the Vegan v2.5-3 package was performed to analyze the microbial communities in different samples, P values were calculated with PERMANOVA-test. The linear discriminant analysis (LDA) effect size (LEfSe) algorithm was performed to identify the significantly abundant genera of bacteria among the different groups (LDA score of >3.5; P < 0.05). Wilcoxon rank-sum test was used to identify the different species in groups of DSS and FCDSS (*P < 0.05, **P < 0.01). Correlations among histopathological score, serum inflammation factors (IL-6,TNF-α, IL-1β, IL-10), number of goblet cells, and the relative abundances of different genera were calculated using Spearman’s analysis.

The raw sequencing reads of this study are openly available in BioProject at https://www.ncbi.nlm.nih.gov/sra/PRJNA1030171, reference number PRJNA1030171.

RNA sequencing

For RNA extraction from the murine intestines, TRIzol® Reagent (Invitrogen) was used under the manufacturer’s directions, followed by the removal of genomic DNA using DNase I (TaK). The preparation of the RNA-seq transcriptome library was achieved with the TruSeqTM RNA sample preparation Kit from Illumina (San Diego, CA). The library was then subjected to sequencing on the Illumina HiSeqxten/NovaSeq 6000 platform, with a read length of 2 × 150 base pairs. The raw paired-end reads were trimmed and quality-controlled by SeqPrep (https://github.com/jstjohn/SeqPrep) and Sickle (https://github.com/najoshi/sickle) with default parameters. The resulting clean reads were aligned to the reference genome in orientation mode using TopHat software. Differential expression genes (DEGs) were identified by calculating the expression of each transcript based on the fragments per kilobase of exon per million mapped reads (FPKM) method. Functional enrichment analysis for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was conducted using Goatools and KOBAS, respectively. The sequence data generated from this study have been deposited in the Gene Expression Omnibus (GEO) database (accession number: GSE254286).

Culture and treatment of Lactobacillus plantarum

Lactobacillus plantarum was cultured as previously described78. Briefly, Lactobacillus plantarum, including AR113 and AR113 Δ1778Δ0467 were sponsored by Professor Wang Guangqiang of the University of Shanghai for Science and Technology. All strains were cultivated anaerobically in deMan, Rogosa, and Sharpe (MRS) medium at 37 °C for 16 h prior to centrifugation (3000 × g for 3 min at 4 °C). The resulting cell pellets underwent two washes with phosphate buffer solution (pH 7.4) and were subsequently reconstituted to a density of approximately 5 × 109 CFU/mL, as ascertained through colony counting on MRS plates, in preparation for subsequent experiments. Each mouse received an oral administration of 1 × 109 CFU of the strains in 0.2 mL (at a concentration of 5 × 109 CFU/mL) via oral gavage daily for 7 d before further treatment, relevant mice treatment was illustrated in Fig. 9B. Lactate levels of various strains were assessed using the GC-MS method.

Histopathology and Immunohistochemistry

After sacrifice, intestinal tissues were fixed in 4% formalin for 24 h and then embedded in paraffin, cut into 4 μm sections for hematoxylin and eosin (H&E) staining. Morphological changes of the colon were assessed by two pathologists in a blinded manner using light microscope (Leica, Germany). Subsequently, the acquired images were subjected to evaluation using Image J software (provided by the US National Institutes of Health, Bethesda, MD). Various parameters, including the degree of inflammatory infiltration, histopathological alterations in crypt structure, ulceration, crypt loss, ulcer presence or absence, and the presence of edema, were quantified, and the histological score was calculated in accordance with established methodologies79,80. Goblet cells were detected through Periodic Acid-Schiff (PAS) staining using standard procedures. To enumerate colonic goblet cells, fixed colonic tissues were further subjected to PAS staining for 10–15 min and subsequent dehydration using 100% alcohol and xylene. Following these steps, images were captured using a microscope (Carl Zeiss AG, Jena, Germany), and the count of acidic mucus-containing goblet cells was conducted and compared across the experimental groups.

Clinical scoring of disease

During treatment, the changes of body weight, diarrhea, and bleeding of mice in each group were observed and recorded daily in the morning. Scoring was performed according to the criteria described by Holger Sann81. Body weight changes were calculated relative to day 1. Total score of the weight loss, diarrhea, and bloody stool was served as the clinical disease score (disease activity index, DAI)81. The following parameters were used for DAI calculation: diarrhea (0 points, normal; 2 points, loose stools; 4 points, watery diarrhea) and hematochezia (0 points, no bleeding; 2 points, slight bleeding; 4 points, gross bleeding).

Immunofluorescence

The antigen of the paraffin-embedded section (4 μm thick) was retrieval with boiling citrate buffer (pH 6.0). Endogenous peroxidase activity was blocked by 3% H2O2 solution at room temperature for 15 min. Sections were then incubated with the primary antibody at 4 °C overnight followed by incubation with fluorescein-labeled secondary antibody(1:100, Yeason, Shanghai) for 30 min. The primary antibody used in this study: Tryptase (1:100, SC-59587, Santa Cruz Biotechnol, USA), FcεRI (1:100, ab229889, Abcam, USA) and Claudin1(1;100, ab125028, Abcam, USA).

ELISA

Serum activities of IL-1β, TNF-α, IL-6, and IL-10 were determined using the Luminex Screening Human Magnetic Assay (R&D Systems, MN, USA). Absorbance was measured using an ELx-800 Universal Microplate Reader (BioTek).

Flow cytometry

Mesentery lymph nodes (MLNs) and spleen were digested to single-cell suspensions with collagenase type D (Roche, Basel, Switzerland) (1 mg/ml) and DNase I (Roche) (0.1 mg/ml) in HBSS at 37 °C for 30 min, and red cells in the preparation were lysed. Flow cytometry (FCM) was performed immediately after washing82. To detect Th17 cell subsets, cells were incubated with 5 ng/ml phorbol myristate acetate and 1 ng/ml ionomycin for 5 h. After 30 min, brefeldin A was added at a final concentration of 10 ng/ml. After washing, cells were stained with CD4-FITC (1 ml/test). After permeating the cells with Cytofix or Cytooperm, cells were stained with IL17A-PE (0.3 ml/test). Treg cells were detected by Cytofix or Cytooperm permeability staining and Foxp3-PE staining (0.3 ml/test). After washing, staining was performed with CD4-FITC (1 ml/test) and CD25-APC (1 ml/test). The cells were then washed with buffer to remove excess stains and analyzed in FCM buffer (Becton Dickinson, San Diego, CA, USA).

Real-time PCR

Total RNA was extracted by Trizol reagent(Invitrogen, USA) according to the manufacturer’s protocol. Then reverse transcription was performed by using the cDNA cycle kit (Invitrogen, USA). The results were standardized to the control values of 18S and control protein. Mixture of SYBR green and the ABI 7300 fast real-time PCR system (Applied Biosystems) was used to display Real-time PCR. The methods of ΔΔCT were performed to calculate the relative gene expression. Primers employed in this study are listed below:

Human-FCER1A-F, CTACTACTGTACGGGCAAAGTGTG.

Human-FCER1A-R, CTGTGTCCACAGCAAACAGAATC.

Human-Tubulin-F, TCTACCTCCCTCACTCAGCT.

Human-Tubulin-R, CCAGAGTCAGGGGTGT-TCAT.

Mouse-Muc2-F, AAACCTCCAACTGAATCCTCG

Mouse-Muc2-R, GAAGTGACGAATGGTGATGTTG

Mouse-NLRP6-F, CTGGCGTCATTGTGGAACCTCT

Mouse-NLRP6-R, TCTCACTCAGCTCCACAGAGGT

Mouse-IL-18-F, AACTTTGGCCGACTTCACTGTA

Mouse-IL-18-R, TATCAGTCATATCCTCGAACACAGG

Mouse-caspase1-F, GGCACATTTCCAGGACTGACTG

Mouse-caspase1-R, GCAAGACGTGTACGAGTGGTTG

Mouse-ASC-F, CTGCTCAGAGTACAGCCAGAAC

Mouse-ASC-R, CTGTCCTTCAGTCAGCACACTG

Mouse-Ang4-F, GTGCCATGGATAAAGGTGTTGAC

Mouse-Ang4-R, CAACTCTGGCTCAGAATGAAAGG

Mouse-RELMβ-F, CGTCTCCCTTTTCCCACTG

Mouse-RELMβ-R, CAGGAGATCGTCTTAGGCTCT

Mouse-ITLN1-F, ACCGCACCTTCACTGGCTTC

Mouse-ITLN1-R, CCAACACTTTCCTTCTCCGTATTTC

Mouse-GAPDH-F, CATCACTGCCACCCAGAAGACTG

Mouse-GAPDH-R, ATGCCAGTGAGCTTCCCGTTCAG

Antibiotic treatment

Enteric germ-free mice were generated as previous described83. Mice were given antibiotic cocktail for 2 weeks. Antibiotic water bottles were inverted every day. The mixture of antibiotic solution applied in this experiment consisted of the following antibiotics: ampicillin (1 g/l, Sangon, China), vancomycin (0.5 g/l, Sangon, China), neomycin (1 g/l, Sangon, China), and metronidazole (1 g/l, Sangon, China).

Mice cohousing

Schematic illustration of the cohousing strategy was demonstrated in Fig. 5A. The experiment involved four distinct groups of mice, comprising of two groups of WT mice and two groups of FC mice. One group of WT and one group of FC mice were individually housed for a duration of 30 days, while another group of WT and FC mice were cohousing for the same period of time. Subsequently, all the mice underwent 1-wk DSS treatment for an additional 1-wk, and were then euthanized at day 10 for the assessment of clinical scores and disease manifestations. Colitis was induced by adding 3% DSS to the drinking water.

Fecal microbiota transplantation

Fecal transplant was performed based on an established protocol84. Briefly, 6–8-wk-old female receiver mice were treated with antibiotic cocktail [vancomycin (0.5 mg/ml), neomycin (1 mg/ml), ampicillin (1 mg/ml), and metronidazole (1 mg/ml)] in their drinking water to generate Enteric germ-free mice. After 2-wk of feeding, stools from FC and WT mice were transferred into antibiotic-treated WT mice respectively. Stools were collected under a laminar flow hood in sterile conditions. Stools from donor mice of each diet group were pooled, and 100 mg was resuspended in 1 ml of sterile saline. The solution was vigorously mixed for 10 s before centrifugation at 800 g for 3 min. The supernatant was collected and transplanted to the germ-free mice by gavage for 2-wk. Supernatant collection and transplantation were described below. Fresh transplant material was prepared on the same day of transplantation within 10 min before oral gavage to prevent changes in bacterial composition. Then experimental acute colitis was induced by giving 3% DSS in the drinking water for 1-wk. After DSS challenge, the mice were euthanized, and the entire colon length was measured.

Colonoids establishment and treatment

Mouse colonoids in our study were extracted and cultured according to the published protocol85. The colon tissue was collected, rinsed gently with ice PBS, and cut into 2 mm segments along the longitudinal axis. The segments were incubated in collagenase IV at 37 °C for 2 h, then filtered and centrifuged to obtain crypts. The pellet obtained was resuspended in basic medium and Matrigel (Corning, USA). Next, 50 μL suspension and 700 μL intestinal organoid growth medium (06005) were added per well to the preheated 24-well plate (Stemcell Technologies, Vancouver, BC, Canada). Replace half of the medium every 2–3 days and pass culture every 5–7 days. After two generations, colonoids were pretreated with or without Lactobacillus plantarum (1 × 106 CFU) Matrigel for 48 h and then treated with TNF (20 ng/ml) for 12 h to induce intestinal damage to the colonoids. Total RNA was extracted with EZ-press RNA purification kit (EZBioscience, Roseville, CA, USA).

Culture and treatment of mast cell line

For IgE crosslinking, rat mast cell line RBL-2H3 were incubated with 1 μg/ml monoclonal murine anti-dinitrophenyl IgE antibody (IgE-DNP, Sigma–Aldrich, USA) (clone: SPE-7) in Dulbecco’s Modified Eagle’s medium (DMEM) containing 10% fetal bovine serum (FBS) overnight. An equal volume of 25 mM lactic acid (LA) in DMEM was added to the cell suspension, resulting in a final cell concentration of 1 × 106 cells/ml, and 12.5 mM LA. The cells were washed twice with RPMI 1640 medium at 350 g for 5 min. Control conditions received DMEM in place of LA. After 1 h of pretreatment in LA media, cells received 50 ng/ml of DNP-HSA (DNP-HSA: Biosearch, USA) (Lot: 102978−01) for 30 min at 37 °C, after which cells and supernatants were collected. Another two groups of cells were washed with RPMI 1640 medium at 350 g for 5 min. Control conditions received DMEM in place of LA. After 1 h of pretreatment in LA media, cells received 20 μg/mL C48/80 (Sigma–Aldrich, USA) (Lot: 097M4042V) for 30 min at 37 °C. The cells and supernatants were collected.

Surface staining with FcεRI flow cytometry

Flow cytometry was performed on a Navios flow cytometer (Beckman, USA), and FlowJo version 10 software (TreeStar) was used for analysis. Cell suspensions were stained with phycoerythrin (PE)/Cy7 anti-mouse FcεRI (Cat#: 134318) and FITC anti-mouse CD117 (Cat#: 105805) (BioLegend, San Diego, CA). The percentage and relative mean fluorescence intensity (rMFI) were analyzed by FlowJo version 10 software.

Bacteriostatic test of mast cell

Oxford cup method

In the ultra-clean workbench, dispatch AR113 into different concentrations of bacteria suspension, using sterile cotton swab to learn apply a suitable amount of bacteria liquid MRS AGAR medium. After that, the sterilized Oxford cup (a circular tube with an inner diameter of 6 nm, an outer diameter of 8 nm, and a height of 10 nm) was placed on the test plate and gently pressurized to make it contact with the petri dish without gaps. 50 microliters of the test sample were injected into the Oxford cup. The size of the inhibition zone was measured after culture for 48 h. The stronger the bacteriostatic effect of the sample to be tested, the larger the bacteriostatic zone.

OD value

The concentration of bacterial suspension is proportional to the transmittance within a certain range, and the transmittance can qualitatively reflect the concentration of microorganisms. The anti-bacterial properties of different samples were judged by comparing the OD values of different groups of bacterial solution after co-culture with different proportions for a certain time. The culture supernatant of mast cells was used and centrifuged at 12,000 rpm for 5 min to remove cell debris. The cell supernatant was diluted in DMEM medium into 4 gradients, in order of 1, 1:10, 1:20, 1:100. AR113 strain was resuscitated and the turbidity of the bacterial solution was adjusted so that OD = 1, and MRS Broth medium was added at 3% ratio. The prepared mast cell culture supernatant was added at 1:1 volume ratio. Absorb 200 ul to detect the initial OD value. After incubating at 35 °C for 48 h, the OD value of 600 nm was detected again.

Statistics

All measurements data were displayed as means ± SEM and then analyzed using GraphPad Prism 8.0 software (San Diego, CA). For the comparison of the two groups, the student t-test was used. Kruskal–Wallis test was used for data that did not meet the normal distribution. Differences were indicated statistically significant at p < 0.05.

The additional materials and methods were provided in the Supplementary materials and methods.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Supplementary information

Supplementary information

Reporting summary

Supplementary information

The online version contains supplementary material available at 10.1038/s41522-024-00563-z.

Acknowledgements

This work was granted by the National Key Research and Development Program of China (No. 2022YFC2009600), the Natural Science Foundation of China (No. 81871267), the National Natural Science Foundation-Youth Foundation (No.82200714), the Natural Science Foundation of China (No. 82270671), Xinyi Digestive Disease Research Fund (No. KY-2023-03-01).

Author contributions

Li Li, Qixiang Mei, and Lianzhong Ai supervised the entire project, provided guidance and resources, and critically revised the manuscript. Yue Yin conceived and designed the study. Yue Yin, Ruilong Wang, and Yanning Li performed experiments, analyzed data, and wrote the manuscript. Letian Pan, and Chenyuan Yan assisted in data collection and analysis. Yusen Hu, Wenfei Qin, and Guangqiang Wang provided technical support. All authors read and approved the final manuscript.

Data availability

The raw data that support the findings of this study are openly available in the SRA database with reference number: PRJNA1030171 and the GEO database with reference number: GSE254286.

Competing interests

The authors declare no competing interests.

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

These authors contributed equally: Yue Yin, Ruilong Wang, Yanning Li.
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