1. Introduction
Crohn’s disease (CD) is a chronic, relapsing inflammatory bowel disease (IBD) characterized by segmental intestinal inflammation and progressive tissue damage [
1]. Dysregulation of host–gut microbiota interactions is widely recognized as a central driver of CD pathogenesis [
2]. Oxidative stress (OS), resulting from an imbalance between oxidants and antioxidant defenses, disrupts redox signaling and induces molecular damage [
3]. Increasing evidence indicates that excessive OS impairs intestinal barrier integrity, alters mucin composition, and enhances bacterial translocation, collectively reshaping gut microbial ecology [
4,
5,
6]. Despite its established role in CD, the upstream epithelial source of reactive oxygen species (ROS) and the downstream ecological consequences for gut microbes remain poorly understood.
In our prior work dissecting the OS-related determinants of CD, several intestinal OS-associated genes were identified that may modulate the development of CD by mediating host–microbiota interactions [
7]. Through a large-scale intestinal transcriptome meta-analysis, dual oxidase 2 (DUOX2)—a member of the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase family responsible for ROS production—was found to be among the most significantly upregulated CD-related OS genes, consistent with previous reports [
8,
9,
10]. DUOX2 produces hydrogen peroxide (H
2O
2), and its chronic activation has been linked to redox imbalance, epithelial barrier disruption, and inflammation [
11]. However, despite these associations, it remains unclear how DUOX2 alters gut microbial composition and whether DUOX2-derived ROS directly shape the luminal microbial ecosystem. Addressing these gaps is essential for determining whether DUOX2 functions as an inflammation-coupled redox amplifier in CD or serves as a modifiable redox node with therapeutic potential.
In this study, the associations among DUOX2 expression, inflammatory readouts, OS indices, and microbial dysbiosis were assessed in intestinal samples from patients with CD and experimental models. Using an intestinal epithelial cell (IEC)-specific Duox2 knockout (KO) mouse model, our findings demonstrate that DUOX2 modulates intestinal inflammation through microbiota-dependent mechanisms. Among the gut microbial alterations, Parabacteroides, particularly P. distasonis, emerged as an ROS-sensitive taxon selectively constrained by DUOX2-derived OS. Mechanistically, DUOX2-dependent H2O2 accumulation constrained P. distasonis growth, as this species exhibited pronounced H2O2 sensitivity, excessive intracellular ROS accumulation, and a lack of key antioxidant enzymes, including peroxide reductase subunit C (AhpC) and superoxide dismutase B (SodB). These findings suggest that epithelial DUOX2-derived ROS establish a luminal redox microenvironment that is inhospitable to these potentially beneficial bacteria. Finally, pharmacological DUOX2 inhibition alleviated experimental murine colitis, reduced OS, and partially restored microbial balance, recapitulating phenotypes observed in Duox2-deficient mice. Collectively, this study aims to define the epithelial DUOX2-mediated orchestration of redox-dependent microbial ecology, identify antioxidant vulnerabilities in DUOX2-sensitive commensals, and highlight DUOX2 as a modifiable redox node with therapeutic relevance for CD.
2. Materials and Methods
2.1. Study Population, Specimen Collection, and Analysis
A total of 46 treatment-naïve patients with CD and 44 normal controls (NCs) were prospectively recruited from the First Affiliated Hospital of Sun Yat-sen University (FAH–SYS) IBD cohort. Specimens from these participants were used for RNA sequencing (RNA-Seq) analysis (
Figure 1A,F,G). Paired terminal ileal and colonic tissue samples were collected from CD patients (inflamed and non-inflamed regions) and NCs. Differential gene expression analysis was performed using the R package DESeq2 (version 1.42.1), with significance thresholds set at
p < 0.05 and |log
2 fold change| > 1. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted using the R package clusterProfiler (v4.10.1).
A validation cohort consisting of 69 patients diagnosed with CD and 32 NCs was enrolled, with human intestinal tissues collected from all participants. The clinical characteristics and disease activity data of the cohort are summarized in
Table S1. These samples were used to obtain the data shown in
Figure 1B,C,E. Disease activity was assessed using the Simple Endoscopic Score for Crohn’s Disease (SES-CD) [
12], serum C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR).
A large paired dataset of intestinal RNA-Seq data and mucosal 16S rRNA sequencing data from patients with CD was obtained from a Dutch cohort (
n = 679) [
13]. Alpha diversity was calculated using the Shannon and Chao1 indices at the genus level. Group differences were assessed using the Mann–Whitney U test. Beta diversity was calculated using Bray–Curtis distance, and the proportion of explained variance (R
2) was assessed via permutational multivariate analysis of variance (PERMANOVA) using the adonis function in the vegan R package v2.6.6.1. A dysbiosis index for each participant was calculated as the median Euclidean distance between their gut microbial composition (genus level) and a reference population; for patients with CD, this represented the distance to all normal controls, with higher values indicating more severe dysbiosis [
14]. Linear regression models were employed to identify genes whose expression levels were significantly associated with dysbiosis scores (false discovery rate, FDR < 0.05). An extreme gradient boosting (XGBoost) model was used to predict dysbiosis scores from gene expression data, and SHapley Additive exPlanations (SHAP) values were calculated using SHAPforxgboost (v0.1.3) to quantify feature importance and directionality. Differential microbial features were identified using linear discriminant analysis effect size (LEfSe).
Single-cell RNA sequencing (scRNA-Seq) data for analyzing DUOX2 expression, including 14 CD samples and 13 control samples, were retrieved from the public database Single Cell Portal [
15]. Cell annotations were obtained from two studies (PREDICT 2021 paper: CD; and PREDICT 2021 paper: FGID), and corresponding cell types were merged for analysis.
2.2. Mouse Strains
Dextran sodium sulfate (DSS)- and 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis models were established using C57BL/6J and BALB/c mice, respectively (GemPharmatech Co., Ltd., Nanjing, China). Villin-Cre mice were obtained from Jackson Laboratory (Bar Harbor, ME, USA), and Duox2 floxed mice on a C57BL/6J background were generated by GemPharmatech Co., Ltd. Mouse genotypes were confirmed via DNA amplification before model construction.
2.3. DSS and TNBS Treatment
For DSS-induced colitis, mice were administered with 2% DSS (MP Biomedicals, Irvine, CA, USA) with a molecular weight (MW) of 36,000–50,000 Da in drinking water ad libitum for 7 days, according to the established protocol [
16]. After DSS solution withdrawal, the disease activity index (DAI) was measured as previously described [
16]. Histological scoring (grades 0–3) was performed on conventional paraffin-embedded, hematoxylin and eosin (H&E)-stained sections by two independent investigators [
16].
TNBS (Sigma-Aldrich, St. Louis, MO, USA)-induced colitis was generated as previously described [
16]. Mice were anesthetized with isoflurane, and 120 μL of 2.5% (
w/
v) TNBS in 50% absolute ethanol was administered intrarectally 7 days after pre-sensitization with 150 μL of 1% (
w/
v) TNBS. Mice were euthanized via cervical dislocation at 3–7 days post-enema, and samples were collected during the active disease phase. Histological assessment was conducted on harvested tissues.
2.4. Quantitative Reverse Transcription–Polymerase Chain Reaction (qRT-PCR)
For human and mouse specimens, total RNA was extracted from cultured cells or tissue biopsies using TRIzol Reagent (Invitrogen, Carlsbad, CA, USA), following the manufacturer’s instructions. RNA concentration and purity were quantified using a NanoDrop 2000 spectrophotometer (Invitrogen, USA). Reverse transcription of RNA to cDNA was performed in vitro using the Transcriptor First Strand cDNA Synthesis Kit (Roche, Basel, BS, Switzerland), and qRT-PCR was conducted with FastStart Universal SYBR Green Master Mix (Roche, Switzerland). Relative gene expression levels were calculated using the delta-delta Ct (ΔΔCt) method, with β-actin as the internal reference gene. All primer sequences used for this assay are listed in
Table S2.
For quantification of bacterial abundance analysis in mouse feces, total DNA was extracted using a DNA Extraction Kit (Magen, Guangzhou, China) according to the manufacturer’s instructions. The relative abundance of target bacterial taxa was measured via qPCR, using the 16S rRNA gene as the internal reference. Primer sequences for these analyses are also listed in
Table S2.
2.5. Western Blotting
Tissue samples were lysed in RIPA buffer (Cell Signaling Technology, Danvers, MA, USA) supplemented with a protease and phosphatase inhibitor cocktail (Invitrogen, USA). SDS-polyacrylamide gel electrophoresis (SDS-PAGE) was performed as previously described [
17]. After electrophoresis, proteins were transferred onto membranes, which were subsequently blocked with skim milk for 1 h at room temperature and then incubated with primary antibodies at 4 °C overnight (anti-DUOX2 antibody, Abcam, Cambridge, UK). Membranes were then incubated with appropriate secondary antibodies for 1 h at room temperature. Immunoblotting signals were visualized with horseradish peroxidase (HRP) substrate (Millipore, Darmstadt, Hessen, Germany) and captured with an iBright FL1500 imaging system (Invitrogen, USA). Tubulin served as the internal reference for normalization. Semi-quantitative band density analysis was conducted using the Image-Pro Plus software (v6.0), and the results are presented as bar charts.
2.6. Immunohistochemistry (IHC) Assay
Tissue sections were prepared from paraffin-embedded human and mouse tissues. After deparaffinization and gradient hydration, the sections were subjected to antigen retrieval; subsequently, they were incubated with 3% hydrogen peroxide for 15 min to expose epitopes and quench endogenous peroxidase activity. Sections were blocked with 3% bovine serum albumin (BSA) in phosphate-buffered saline (PBS) for 1 h at room temperature, then incubated with the primary antibody overnight at 4 °C (anti-DUOX2 for human: 1:400 dilution; anti-DUOX2 for mouse: 1:200 dilution, Abcam, UK). After three washes with PBS containing 0.1% Tween-20, sections were incubated with HRP-conjugated secondary antibodies (Cell Signaling Technology, USA) for 30 min at room temperature. Following counterstaining with hematoxylin, serial ethanol dehydration, and coverslip mounting, images were captured using a Leica DMI1 microscope (Leica Microsystems, Wetzlar, Germany).
2.7. In Vivo Intestinal Permeability Assessment
Fluorescein isothiocyanate-dextran (FD4; MW 4000 Da; Sigma-Aldrich, St. Louis, MO, USA) was administered via oral gavage at a dosage of 22 mg·kg−1 after the mice were fasted for 4 h. Blood was collected via orbital extirpation and centrifuged at 1900× g for 10 min. The supernatant was further centrifuged again at 16,000× g for 10 min. Plasma samples and gradient-diluted FD4 standards were measured using a Spectra Max M5 microplate reader (Molecular Devices, San Jose, CA, USA) at excitation/emission wavelengths of 490/530 nm.
2.8. Oxidative Stress Index Assays
H2O2 levels in intestinal epithelial cells were quantified using the Amplex Red Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA), following the manufacturer’s instructions. Fluorescence intensity was measured with a multi-mode microplate reader (excitation 530–560 nm; emission 590 nm).
ROS levels were assessed using sample-type-specific methods. For tissue sections, dihydroethidium (DHE) staining was performed. Frozen sections were thawed, incubated with DHE solution (1:500, Servicebio, Wuhan, China) in the dark for 20–30 min at 37 °C, rinsed with PBS, and visualized using an Olympus BX-63 microscope (Olympus, Tokyo, Japan). ROS levels were semi-quantified by measuring the mean fluorescence intensity using the ImageJ software (v1.52a). For cultured cells and microbes, ROS levels were measured using 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) (MCE, Shanghai, China) in accordance with standard protocols.
Superoxide dismutase (SOD) levels in specimens were measured using an SOD Assay Kit (Beyotime Biotechnology, Shanghai, China). Assays were performed according to the manufacturer’s instructions, and SOD activity was calculated from absorbance readings at 560 nm.
2.9. Cell Culture and Adenovirus Transfection
NCM460 cells, a human normal colonic mucosal epithelial cell line (INCELL, San Antonio, TX, USA), were cultured in M3: BaseF medium (INCELL, USA) supplemented with 10% fetal bovine serum and 1× penicillin–streptomycin (Invitrogen, USA) in a 5% CO2 atmosphere at 37 °C.
Adenovirus for DUOX2 overexpression and negative control constructs were designed and generated by Genecopoeia Inc. (Shanghai, China). Cells were transfected with adenovirus according to the manufacturer’s instructions using a pre-optimized multiplicity of infection (MOI). Fresh complete medium was replaced at 12–24 h post-transfection. Transfection efficiency was evaluated using fluorescence microscopy at 24–48 h post-transfection. Transient DUOX2 overexpression lasted for approximately 7 days.
2.10. Cohousing Experiment
Age- and sex-matched wild-type (WT) and Duox2 KO mice from the same breeders were assigned to either separate housing or cohousing for 3–4 weeks. After this period, all mice were subjected to DSS-induced colitis modeling.
2.11. Antibiotic Cocktail (ABX) Experiment
Age- and sex-matched WT and Duox2 KO mice from the same breeders were assigned to separate housing and administered a six-antibiotic cocktail (1000 mg kanamycin, 87.5 mg gentamicin, 142.5 mg colistin, 537.5 mg metronidazole, 112.5 mg vancomycin, and 25 mg erythromycin dissolved in 2.5 L distilled water) for 14 days to deplete their gut microbiota. All antibiotics were purchased from Maclin Inc. (Shanghai, China).
2.12. Fecal Microbiota Transplantation (FMT) Experiment
Age- and sex-matched WT and Duox2 KO mice assigned to separate housing were first treated with the six-antibiotic cocktail described above to deplete their gut microbiota. Each mouse was administered 200 μL of a PBS suspension containing feces from either WT or DUOX2 KO donor mice via oral gavage. Three days after FMT, all mice underwent DSS-induced colitis modeling.
2.13. Microbial Strains and Culturing Conditions
Two strains of Parabacteroides distasonis (ATCC BAA-1295, ATCC 8503) were purchased from the Guangdong Microbial Culture Collection Center (Guangzhou, China) and cultured anaerobically at 37 °C in BHC medium. Escherichia coli strain MG1655 was cultured under the same anaerobic conditions.
To establish a bacterial OS model, BHC medium was supplemented with H2O2 at final concentrations of 0.2, 0.5, and 1.0 mM. After 24 h of anaerobic incubation at 37 °C, bacterial growth was monitored by OD600 values.
2.14. Fecal DNA Extraction and 16S rRNA Sequencing
Fecal samples were collected from Duox2 KO mice and their WT littermates. DNA was extracted using the FastPure Stool DNA Isolation Kit (MJYH, Beijing, China) according to the manufacturer’s instructions. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified by PCR using bacterial universal primers 341F (5′–CCTACGGGNGGCWGCAG–3′) and 806 R (5′–GGACTACHVGGGTATCTAAT–3′). Amplicons were excised from 2% agarose gels, purified with the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), and quantified using an ABI StepOnePlus Real-Time PCR System (Life Technologies, Carlsbad, CA, USA). Purified amplicons were pooled in equimolar amounts and paired-end sequenced (PE250) on an Illumina platform according to standard protocols.
Raw sequences were demultiplexed, quality filtered with fastp (v0.19.6) [
18], and merged using FLASH (v1.2.11) [
19]. High-quality sequences were denoised using DADA2 [
20] in QIIME2 (v2020.2) [
21] to generate amplicon sequence variants (ASVs). Sequencing depth was normalized by rarefying samples to 20,000 sequences per sample, achieving an average Good’s coverage of 97.90%. Taxonomic assignment was performed in QIIME2 using a naïve Bayes classifier against the SILVA 16S rRNA database. Bioinformatics analysis of the gut microbiota was carried out using the Majorbio Cloud platform, and alpha diversity, beta diversity, and LEfSe analyses were performed as described previously.
2.15. Shotgun Metagenomic Sequencing
Fecal DNA quality, concentration, and purity were assessed using a SynergyHTX, NanoDrop2000, and 1% agarose gel electrophoresis. DNA was fragmented to ~350 bp using the Covaris M220 (Gene Company Limited, Hong Kong, China), libraries were constructed with the NEXTFLEX Rapid DNA-Seq Kit, and sequencing was performed on an Illumina NovaSeq™ X Plus using the NovaSeq X Series 25B Reagent Kit (Majorbio, Shanghai, China).
Raw metagenomic reads were processed on the Majorbio Cloud Platform. Adapter trimming and quality control were performed using fastp (v0.23.0), and host DNA was removed using BWA [
22] (v0.7.17). Clean reads were assembled with MEGAHIT (v1.1.2) [
23], retaining contigs ≥ 300 bp. Open reading frames (ORFs) were predicted using Prodigal (v2.6.3) [
24] and clustered into a non-redundant gene catalog using CD-HIT (90% sequence identity, 90% coverage) [
25]. Gene abundance was estimated using SOAPaligner at 95% identity [
26].
For functional profiling of OS, high-quality reads filtered by KneadData v0.12.0 were aligned against the SEED database using translated homology search and annotated to subsystems and functional levels 1–3 using Super-Focus [
27].
2.16. Single-Cell RNA Sequencing
Two
Duox2 KO mice and two WT mice were used. Isolation of murine intestinal epithelial cells was performed as described previously [
28]. Single-cell barcoding was performed using a Chromium Single-Cell Controller (10× Genomics, Pleasanton, CA, USA), and reverse transcription was carried out using an S1000 Touch Thermal Cycler (Bio-Rad, Hercules, CA, USA). Libraries were prepared and sequenced on an Illumina NovaSeq 6000 sequencer (Illumina, San Diego, CA, USA). After read processing and quality control, cells were clustered using Seurat v3.1 with SCTransform normalization, and cell clusters were visualized via uniform manifold approximation and projection (UMAP) plots. Functional enrichment analysis was performed using Gene Ontology (GO) analysis.
2.17. Protein Extraction and Astral DIA Proteomics Sequencing
Three Parabacteroides distasonis ATCC BAA-1295 (PD1) and three Escherichia coli MG1655 (EC) samples were prepared for proteomic sequencing analysis. Cultures were grown to the logarithmic phase, centrifuged at 5000× g for 10 min at 4 °C, and the pellets were washed twice with pre-cooled sterile PBS and stored at −80 °C for further use.
Proteins were extracted using lysis buffer and quantified with using a BCA Protein Assay Kit (P0012, Biocentury, Shanghai, China). The quality of the extracted proteins was evaluated through SDS-PAGE and Coomassie Brilliant Blue R-250 staining. Mixed samples containing 15 μg of protein from each sample were prepared for database construction and quality control. All samples underwent trypsin digestion via filter-aided sample preparation [
29], were desalted with C18 cartridges, and the resulting peptides were lyophilized and reconstituted in 0.1% formic acid. Each sample was supplemented with indexed retention time (iRT) peptides, which were added for data-independent acquisition (DIA) calibration. Peptides were analyzed using a nanoscale Vanquish Neo UHPLC system (Thermo Scientific, Waltham, MA, USA) in DIA mode coupled with an Astral high-resolution mass spectrometer (Thermo Scientific, USA). In the first stage of mass spectrometry (MS), precursor ions were scanned over a mass range spanning 380 to 980
m/
z at a resolution of 240,000 (200
m/
z), with a normalized automatic gain control (AGC) target of 500% and an injection time of 5 ms. In the second stage of MS, the DIA scans utilized 300 scanning windows (2
m/
z isolation width), and higher-energy collisional dissociation was applied at 25 eV, a normalized AGC target of 500%, and a maximum injection time of 3 ms.
DIA-NN (v1.9.2) was used for data analysis with trypsin digestion (maximum missed cleavage of 1), carbamidomethyl© as a fixed modification, and oxidation (M) and N-terminal acetylation as variable modifications. Proteins were reported at a 99% confidence level and an FDR of ≤0.01, confirmed via the UniProt database.
Data were analyzed using Personalbio Genescloud (
www.genescloud.cn). Principal component analysis (PCA) was used to visualize group differences. Differential analysis between two groups was performed using a
t-test with significance thresholds of
p < 0.05 and fold change of FC ≥2 or ≤0.5. Functional enrichment analysis was conducted using the R package clusterProfiler (v4.10.0).
2.18. Statistical Analysis
Data were analyzed using the GraphPad Prism 9.0 software (GraphPad Software Inc., San Diego, CA, USA) and IBM SPSS Statistics 23 (IBM Corp., Armonk, NY, USA). Values are presented as the mean ± standard error of the mean (SEM). For normally distributed data, group comparisons were performed using an unpaired, two-tailed Student’s t-test or one-way analysis of variance (ANOVA). Non-normally distributed data were analyzed with the Mann–Whitney U-test and Kruskal–Wallis test. Spearman correlation was calculated to evaluate the relationship between DUOX2 expression and disease activity. p < 0.05 was considered statistically significant.
4. Discussion
CD is characterized by chronic intestinal inflammation driven by dysregulated host–microbiome interactions and intestinal immune dysregulation, with OS increasingly recognized as an upstream contributor to epithelial intestinal barrier disruption and microbial imbalance [
2,
4,
37]. DUOX2 is consistently upregulated in patients with CD and represents a major epithelial source of ROS. However, whether DUOX2-derived OS actively shapes gut microbial ecology—and thereby contributes to CD progression—remains unclear. In this study, by integrating human multi-omics analyses, IEC-specific
Duox2 knockout mice, in vitro bacterial redox assays, and pharmacological intervention, we address this knowledge gap and propose a mechanistic framework in which epithelial DUOX2 drives a redox-dependent shift in microbial ecology that amplifies intestinal inflammation.
Our findings extend prior observations identifying
DUOX2 as one of the most strongly induced OS-related genes in CD mucosa. Although genome-wide association studies (GWAS) have not classified
DUOX2 as a canonical CD risk gene, accumulating evidence links
DUOX2 to IBD susceptibility [
38,
39,
40]. Our previous large-scale transcriptomic meta-analysis further underscored
DUOX2 as one of the most prominently upregulated OS-related genes in CD intestinal tissues [
7]. Building on this, the current study integrates transcriptomic and microbial sequencing data to validate a more consistent association between elevated
DUOX2 expression and microbial dysbiosis. Specifically, high-
DUOX2 individuals exhibited an altered microbial composition, with depletion of beneficial anaerobes and enrichment of ROS-tolerant pathobionts. In addition, high-
DUOX2 individuals exhibited upregulation of pro-inflammatory pathways. Given the well-established bidirectional relationship between intestinal inflammation and microbiota homeostasis, these findings underscore the ecological relevance of DUOX2-mediated redox imbalance in CD pathogenesis [
41]. Notably, bioinformatics modeling further demonstrated that DUOX2 expression could reliably predict the degree of microbial dysbiosis in patients with CD, supporting the notion that DUOX2 functions as an upstream determinant of mucosal redox balance with broad ecological and immunological consequences, rather than merely reflecting inflammatory status. Nevertheless, it is critical to acknowledge that these observations reflect correlative associations derived from cross-sectional transcriptomics data; as such, a definitive causal relationship between
DUOX2 expression and microbial dysbiosis in human CD cannot be established, and the directionality of this interaction remains strictly inferential at this stage.
To further delineate the functional role of DUOX2 in intestinal homeostasis and disease susceptibility, we generated an IEC-specific
Duox2 KO mouse model. Phenotypic analyses revealed that DUOX2 ablation conferred marked protection against experimental colitis and altered the intestinal OS profile. These loss-of-function findings complement and extend previous gain-of-function studies in TLR4-driven DUOX2 transgenic mice, in which DUOX2 overexpression exacerbated epithelial barrier dysfunction and subclinical inflammation [
11]. Together, these reciprocal genetic approaches support a causal role for DUOX2 in promoting intestinal inflammation through the disruption of redox homeostasis and epithelial barrier integrity.
Importantly, the cohousing and FMT experiments demonstrated that the protective phenotype associated with DUOX2 deletion is microbiota-dependent and transmissible. These findings establish a functional pathway in which epithelial DUOX2 activity shapes gut microbial composition, thereby modulating host susceptibility to inflammation. When combined with epithelial single-cell transcriptomics data indicating reduced stress response and pathogen-sensing signatures, these results position DUOX2 as a key architect of the intestinal microbial ecosystem.
Multi-omics analyses across mouse and human datasets converged on Parabacteroides, particularly P. distasonis, as a DUOX2-sensitive effector taxon. Depletion of Parabacteroides was consistently observed in high-DUOX2 patients, WT mice, and DUOX2-overexpressing contexts, whereas enrichment was evident in DUOX2-deficient mice and low-DUOX2 human samples. Functional validation demonstrated that oral administration of P. distasonis significantly ameliorated DSS-induced colitis and improved epithelial barrier integrity, supporting its role as a protective commensal that is selectively disadvantaged under DUOX2-driven oxidative conditions. This cross-species convergence identifies P. distasonis as a key microbial mediator of DUOX2-associated ecological imbalance.
Parabacteroides is a core taxon of the human gut microbiota and has been widely reported to exert beneficial effects, including modulation of mucosal immunity, attenuation of inflammation, and support of carbohydrate metabolism, leading to its recognition as a promising probiotic candidate [
33,
34,
42]. Previous studies have reported reduced
Parabacteroides abundance in patients with IBD, with
P. distasonis showing particularly pronounced depletion in inflamed mucosal tissues [
33,
43]. Our findings extend these findings by demonstrating that
P. distasonis supplementation can mitigate intestinal inflammation and restore epithelial barrier function, reinforcing its therapeutic relevance in IBD contexts.
Mechanistically, our study pursued two complementary lines of investigation: first, metagenomic analyses revealed that DUOX2 ablation was associated with altered microbial OS-response profiles, with
Parabacteroides consistently linked to lower microbial OS signatures. These data suggest that DUOX2-driven redox conditions shape the intestinal OS microenvironment in a manner that is unfavorable for
Parabacteroides persistence. Second, in vitro experiments directly validated this relationship, showing that elevated H
2O
2 concentrations markedly inhibited
P. distasonis growth, induced morphological damage, and increased intracellular ROS accumulation. Proteomic profiling further elucidated the molecular basis of this sensitivity: unlike H
2O
2-tolerant
E. coli,
P. distasonis lacked key antioxidant enzymes, particularly AhpC and SodB. AhpC is well established as a primary H
2O
2 scavenger in many gut commensals [
44,
45], and its absence has been shown to result in rapid ROS accumulation and cellular damage in bacterial systems [
46]. The deficiency of these detoxification pathways in
P. distasonis provides a plausible mechanistic explanation for its selective depletion under DUOX2-mediated oxidative conditions.
While the downstream protective mechanisms provided by P. distasonis to the host are not the primary focus of this study, we have obtained preliminary data supporting potential functional pathways. Specifically, both in vitro and in vivo experiments confirmed that P. distasonis exerts a colitis-alleviating effect by restoring mucosal barrier function, which provides preliminary validation of its host-associated protective mechanisms. Additionally, metabolomic analysis revealed that P. distasonis may further regulate mucosal barrier integrity and influence colitis progression by modulating bile acid metabolism, proline metabolism, and other relevant pathways. Future studies will aim to delineate the precise molecular cascades underlying these metabolic and barrier-modulating effects, as well as their functional crosstalk, in order to fully exploit the therapeutic potential of P. distasonis in CD.
Finally, pharmacological inhibition of DUOX2 using Compound 521 recapitulated key features of genetic DUOX2 deletion, including reduced epithelial ROS levels, attenuation of colitis severity, and partial restoration of beneficial microbial taxa such as P. distasonis. These results nonetheless highlight the therapeutic potential of targeting DUOX2 to modulate mucosal redox balance and restore gut microbial homeostasis, with the caveat that potential off-target effects and NOX-family cross-reactivity of Compound 521 were not experimentally validated in our in vivo studies. Beyond DUOX2 inhibition, our findings also suggest the possibility of leveraging ROS-sensitive commensals such as P. distasonis as next-generation probiotics for the management of intestinal inflammation. Given the intrinsic sensitivity of P. distasonis to ROS, restoring a normoxidative intestinal niche is an essential prerequisite for its colonization and subsequent therapeutic efficacy in colitis. A rational sequential therapeutic strategy is therefore proposed, wherein patients first receive conventional anti-inflammatory interventions (e.g., anti-TNF-α therapy) or DUOX2-targeted therapy to alleviate intestinal oxidative inflammation and normalize the microenvironment, followed by P. distasonis supplementation to further rebalance the dysregulated gut microbiota. Notably, treatment with anti-TNF-α, DUOX2 inhibition, and P. distasonis supplementation may be clinically relevant, especially in patients who develop resistance to anti-TNF-α therapy. This therapeutic paradigm merits further investigation.
Collectively, this study reveals a previously unrecognized mechanism by which epithelial DUOX2 shapes gut microbial ecology through redox-dependent niche selection, thereby exacerbating intestinal inflammation. Mechanistically, it establishes DUOX2 as a proximal regulator of gut homeostasis acting through microbial ecological remodeling, rather than exclusively through immune-mediated pathways. Therapeutically, it supports DUOX2 inhibition and restoration of ROS-sensitive beneficial taxa (e.g., P. distasonis) as potential strategies for the treatment of CD. Conceptually, it underscores the importance of epithelial-derived ROS as a selective ecological force governing microbial community structure.
This study has several limitations. First, although P. distasonis emerged as a dominant DUOX2-sensitive effector taxon, the roles of other Parabacteroides species warrant further investigation. Second, while we identified the absence of AhpC and SodB as a key contributor to P. distasonis H2O2 sensitivity, the downstream mechanisms underlying this bacterial growth arrest were not fully elucidated; targeted genetic manipulation of these antioxidant pathways would provide valuable mechanistic insight. Finally, although previous studies have shown that microbiota can induce DUOX2 expression, our work demonstrates the reciprocal effect of DUOX2 on microbiota composition. Dissecting the directionality and feedback dynamics of this bidirectional crosstalk in CD remains an important challenge for future research.
In conclusion, this study establishes a mechanistic link between the epithelial DUOX2–ROS–microbiota axis and colitis susceptibility. Integrating human and mouse multi-omics data with mechanistic functional analyses, we identified DUOX2 as a key epithelial regulator of redox-driven microbial ecology and intestinal inflammation. Therefore, targeting DUOX2 or leveraging ROS-sensitive beneficial microbes represents a promising, mechanism-based therapeutic strategy for CD.