In vitro and in vivo anti-inflammatory activity of oenothein B from Eucalyptus leaves and its amelioration mechanism on colitis in mice by regulating fecal microbiota and metabolism

Abstract

Nonvolatile extracts from Eucalyptus leaves possess diverse bioactivities; however, their anti-inflammatory potential and key active components remain insufficiently characterized. In this study, we demonstrated that antioxidant polyphenols extracted from Eucalyptus grandis × E. urophylla (EPEGU) using low-temperature continuous phase transformation extraction (LCPTE) exhibited significant anti-inflammatory effects by suppressing the secretion of nitric oxide (NO), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6). Furthermore, oenothein B (OEB), isolated from EPEGU, markedly reduced pro-inflammatory cytokine levels and their corresponding mRNA expression in LPS-stimulated RAW264.7 macrophages. In vivo, OEB administration alleviated ulcerative colitis (UC) symptoms in mice, evidenced by attenuation of body weight loss, prevention of colon shortening, reduction of pro-inflammatory mediator secretion, and improvement in spleen weight, disease activity index (DAI), histopathological damage, and oxidative stress markers. Gut microbiota analysis revealed that OEB mitigated dysbiosis by increasing the abundance of beneficial taxa such as Firmicutes, Akkermansia, Lactobacillus, and Ruminococcus, while reducing potentially pathogenic genera including Proteobacteria, Bacteroides, and Escherichia–Shigella. These microbial shifts were associated with alterations in colonic metabolites, primarily involving arachidonic acid and bile acid metabolism. Collectively, these findings indicate that OEB is a promising natural anti-inflammatory agent and potential adjuvant for the prevention and management of inflammatory bowel diseases.

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1 Introduction

Ulcerative colitis (UC) is a chronic inflammatory disorder of the colon with a multifactorial etiology involving genetic predisposition, environmental influences, lifestyle factors, and gut microbiota imbalance.¹ Clinically, UC is characterized by bloody stools, diarrhea, weight loss, and compromised intestinal health. Alarmingly, both the incidence and prevalence of UC have continued to rise globally.² Conventional treatments, including immunosuppressants, interferons, and glucocorticoids,³ provide symptomatic relief but fail to achieve a definitive cure. Prolonged use of these agents often results in significant adverse effects and a high risk of disease relapse. Consequently, there is an urgent need for safer and more effective therapeutic strategies for both the prevention and management of UC.

Emerging evidence indicates that gut microbiota dysbiosis and associated metabolic disturbances play a pivotal role in UC progression. Dysbiosis is marked by altered microbial composition and abundance,⁴ including an increased presence of pathogenic bacteria such as Proteobacteria and Bacteroides, alongside a significant reduction in beneficial bacteria such as Lactobacillus and Bifidobacterium.⁵ This imbalance contributes to metabolic disruptions, notably elevated levels of lipopolysaccharides and reduced short-chain fatty acids, which exacerbate intestinal oxidative stress and inflammation. Maintaining microbial homeostasis is thus considered a promising therapeutic target in UC. Recent studies have shown that natural polyphenols can alleviate UC symptoms by modulating gut microbiota composition.^6,7 Identifying polyphenol-rich natural compounds may therefore offer a novel and effective approach for UC prevention and therapy.

The genus Eucalyptus, native to Australia, is widely distributed across tropical and subtropical regions. Various Eucalyptus species have long been used in traditional medicine systems in Australia, China, India, and parts of Europe for treating diverse ailments.⁸ Notably, several species indigenous to the Dharawal region of Australia have been traditionally employed to manage inflammatory conditions, as documented in the Dharawal Pharmacopeia.^9,10 Modern pharmacological studies have extensively demonstrated the anti-inflammatory activity of volatile oils extracted from Eucalyptus leaves.^11,12 More recently, research has shifted toward the investigation of nonvolatile extracts, which are rich in bioactive compounds such as polyphenols, flavonoids, terpenoids, and tannins.^13,14 These nonvolatile constituents have shown promising antioxidant, antimicrobial, and anti-aging properties. However, the anti-inflammatory potential of these nonvolatile fractions, as well as the identification of specific active components responsible for these effects, remains underexplored. In recent work, our team developed a nonvolatile Eucalyptus leaf extract enriched in phenolic compounds, referred to as Eucalyptus Polyphenol Extract (EPE). EPE has demonstrated strong antioxidant activity, modulation of gut microbiota, and improvements in meat quality.^15,16 Despite these promising properties, its anti-inflammatory effects have yet to be evaluated.

To address this gap, the present study aimed to assess the anti-inflammatory potential of EPE and identify its key active components. Initially, the optimal Eucalyptus resource was selected from three economically important species using various extraction methods, with antioxidant capacity as the primary selection criterion. The anti-inflammatory activity of EPE was then evaluated in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. Subsequently, bioactivity-guided fractionation was performed to isolate the principal anti-inflammatory constituents, whose efficacy and mechanisms of action were further examined in a dextran sulfate sodium (DSS)-induced colitis mouse model. This study provides new insights into the anti-inflammatory potential of Eucalyptus leaf polyphenols and supports the development of EPE as a promising natural agent for the prevention and management of inflammatory bowel diseases.

2 Materials and methods

2.1 Reagents

Eucalyptus leaves from E. grandis × E. urophylla, E. tereticornis, and E. urophylla, representing economically significant forest species, were collected from the Leizhou Forestry Bureau, Zhanjiang, Guangdong Province, China. RAW264.7 murine macrophages were obtained from the Kunming Cell Bank of the Chinese Academy of Sciences. Dulbecco's modified Eagle's medium (DMEM; cat. no. 11965092), fetal bovine serum (FBS; cat. no. A5670201), dexamethasone (DXM; cat. no. D4902), phosphate-buffered saline (PBS, pH 7.4; cat. no. 10010023), and antibiotics (Streptomycin–Penicillin; cat. no. 15140122) were purchased from Gibco (Waltham, MA, USA). LPS (cat. no. SMB00610), 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT; cat. no. 475989), and ascorbic acid (cat. no. 1043003) were obtained from Sigma-Aldrich (St Louis, MO, USA). A nitric oxide (NO) assay kit (cat. no. S0021S) was provided by Beyotime Biotechnology (Shanghai, China). Mouse ELISA kits for interleukin-6 (IL-6) (cat. no. EMC004.96), interleukin-1β (IL-1β) (cat. no. EMC001b.96), and tumor necrosis factor-α (TNF-α) (cat. no. EMC102a.96) were purchased from Neobioscience Technology Co., Ltd (Shenzhen, China). Assay kits for superoxide dismutase (SOD; cat. no. A001-3-2), catalase (CAT; cat. no. A007-1-1), glutathione peroxidase (GPx; cat. no. A005-1-2), and malondialdehyde (MDA; cat. no. A003-1-2) were obtained from the Jiancheng Biotechnology Institute (Nanjing, China). DSS (cat. no. MFCD00081551) was sourced from MP Biomedicals (Santa Ana, CA, USA). All other reagents were of analytical grade and used as received.

2.2 Sample preparation and isolation of bioactive components

After drying, eucalyptus leaves were pulverized and passed through a 40-mesh sieve. Three extraction methods—solvent extraction (SE), ultrasonic wave-assisted extraction (UWE), and low-temperature continuous phase transformation extraction (LCPTE)—were carried out using 70% (v/v) ethanol to evaluate their effects on extraction efficiency, total polyphenol content, and antioxidant activity.¹⁷ For SE, the leaf powder was extracted twice with 70% ethanol at 50 °C for 2 h using magnetic stirring. For UAE, two extraction cycles were performed with 70% ethanol at 50 °C for 2 h using ultrasonic equipment. For LCPTE, the extraction was conducted using 70% ethanol under a pump flow rate of 35 L h⁻¹ at 50 °C for a total of 2 h. All resulting extracts were vacuum-concentrated and spray-dried under the following conditions: inlet temperature 180 °C, outlet temperature 80 °C, and atomizer speed 12 000 rpm.

The optimal eucalyptus leaf polyphenol extract was dissolved in 70% ethanol at a concentration of 200 mg mL⁻¹ and stored at 4 °C for 24 h. Following sedimentation, the supernatant was sequentially partitioned with petroleum ether (fraction 1) and ethyl acetate (fraction 2); the remaining aqueous phase was designated as fraction 3. After assessing in vitro anti-inflammatory activity across all fractions, fraction 2 was identified as optimal and subsequently analyzed by high-performance liquid chromatography (HPLC) and further purified using preparative HPLC (LC-8A, Shimadzu). All lyophilized extracts and fractions were stored at −20 °C for subsequent experiments.

2.2.1 HPLC analysis. The eucalyptus leaf polyphenol extract was separated using a Diamonsil C18 column (250 × 4.6 mm, 5 μm) and analyzed by HPLC coupled with a photodiode array detector (HPLC-PDA; LC-15C, Shimadzu, Japan). A gradient elution was performed using 0.2% (v/v) phosphoric acid in HPLC-grade water (solvent A) and methanol (solvent B), progressing from 10% to 90% solvent B over 0–70 min at a flow rate of 1 mL min⁻¹. Prior to injection, all samples were filtered through 0.22 μm nylon membranes (Jin Teng Experimental Equipment Co., Ltd, Tianjin, China).

2.2.2 Scavenging activity of the hydroxyl radical (˙OH). The hydroxyl radical (˙OH) scavenging activity was determined according to the method described by Giese et al.¹⁸ The reaction mixture consisted of 0.5 mL of 1.5 mmol L⁻¹ FeSO₄, 0.35 mL of 6 mmol L⁻¹ H₂O₂, 0.15 mL of 20 mmol L⁻¹ sodium salicylate and 0.5 mL of sample solution at various concentrations. After incubation at 37 °C for 1 h, the absorbance was measured at 562 nm (A1). A mixture in which the sample was replaced with deionized water was used as a blank (A0), while a solution in which H₂O₂ was replaced with deionized water was used as a reference (A2). Ascorbic acid was used as the positive control.

2.2.3 ABTS⁺ radical-scavenging assay. The scavenging activity of 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS⁺) radicals was determined according to the method described by Smolskaite et al.¹⁹ The reaction mixture consisted of 0.9 mL of sample solution at various concentrations and 0.1 mL of ABTS⁺ radical solution (adjusted to an absorbance of 0.75 ± 0.01 at 734 nm). After incubation for 6 min at room temperature, the absorbance was measured at 734 nm (A1). PBS was used as the blank (A0), and ascorbic acid served as the positive control.

2.3 Cell culture

RAW 264.7 macrophages were maintained in DMEM supplemented with 10% fetal bovine serum and 1% antibiotics at 37 °C in a humidified incubator under 5% CO₂.

2.3.1 Cell viability assay. Cell viability was assessed using the MTT assay. RAW264.7 macrophages (1.0 × 10⁴ cells per well) were seeded into 96-well plates and incubated for 24 h. Following incubation, the culture medium was replaced with sample solutions at various concentrations and further incubated for 24 h. Subsequently, 100 μL of MTT solution (0.5 mg mL⁻¹ in PBS) was added to each well, and the cells were incubated for an additional 4 h. The resulting formazan crystals were solubilized with 150 μL of dimethyl sulfoxide (DMSO) per well. Absorbance was then measured at 490 nm using a multiscan spectrophotometer (Thermo Labsystems, USA) to determine cell viability.

2.3.2 Measurement of NO, TNF-α, IL-1β and IL-6 levels in RAW 264.7 cells. RAW264.7 macrophages (2.0 × 10⁴ cells per well) were seeded into 96-well plates and incubated for 24 h. Subsequently, the cells were treated with sample solutions for an additional 24 h. After treatment, the cells were washed with PBS and stimulated with LPS (1 μg mL⁻¹) at 37 °C for 24 h. Untreated cells were used as the control group. The culture supernatant was then collected, and the levels of NO, TNF-α, IL-1β, and IL-6 were quantified using an NO assay kit and ELISA kits (Beyotime Biotechnology, China), following the manufacturer's instructions.

2.3.3 Quantitative real-time PCR analysis. Total RNA was extracted from macrophages and reverse-transcribed into cDNA using a commercial kit (Tiangen Biotech Co., Ltd, Beijing, China). Quantitative real-time PCR (RT-qPCR) was performed using specific primers (Table S1). Each 10 μL reaction mixture contained 0.4 μL of each primer (10 μmol), 1 μL of cDNA, 5 μL of SYBR green master mix, and 3.2 μL of ROX reference dye. Amplification was carried out on a LightCycler480 system (Roche, Switzerland). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the internal reference, and relative gene expression levels were calculated using the 2^−ΔΔct method.

2.4 Animal experiment design

A total of 40 male C57BL/6J mice (6–8 weeks old, 18–21 g) were obtained from Zhejiang Weitong Lihua Laboratory Animal Technology Co., Ltd (Zhejiang, China). All animals were housed under standard conditions (25 ± 1 °C, 50 ± 5% humidity) for one week prior to the experiment. The study protocol was approved by the Animal Ethics Committee of South China Agricultural University (SYXK-2019-0136).

The mice were randomly assigned to four groups: control, model, low-dose OEB (L-OEB, 25 mg kg⁻¹), and high-dose OEB (H-OEB, 100 mg kg⁻¹). As illustrated in Fig. 7A, OEB was administered via oral gavage once daily for 27 days in the treatment groups, while the control and model groups received sterile water. From day 22 to day 27, 2% DSS was added to the drinking water of all groups except the control to induce ulcerative colitis. Body weight, stool consistency, and the presence of blood in feces were recorded daily during DSS administration. On day 27, the mice were weighed and euthanized. Spleens were harvested and weighed to calculate the spleen index. Colon tissues and fecal samples were collected and stored at −80 °C for further analysis.

2.4.1 Assessment of the disease activity index (DAI). The DAI was assessed based on body weight loss, stool consistency, and fecal bleeding, following a slightly modified method described previously.²⁰

2.4.2 Histopathological assay and scores. Colon tissue fragments were fixed in 4% formalin, dehydrated, embedded in paraffin, sectioned, and stained with hematoxylin and eosin (H&E). The stained sections were examined and photographed under an optical microscope at 200× magnification. Histopathological scoring was performed according to previously described methods.⁵

2.4.3 Anti-inflammatory and antioxidant status. Colon levels of inflammatory markers (TNF-α, IL-1β, IL-6) and antioxidant indicators (SOD, CAT, GPx, MDA) were measured using commercial assay kits, following the manufacturer's instructions.

2.4.4 16S rDNA sequencing of gut microbiota. Fecal samples were collected from six mice per group for gut microbiota analysis. Bacterial DNA was extracted from fecal content using the E.Z.N.A.® soil DNA kit (Omega Bio-tek, Norcross, GA, USA), following the manufacturer's protocol. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using specific primers (338F: 5′-ACTCCTACGGGAGGCAGCAG-3′ and 806R: 5′-GGACTACHVGGGTWTCTAAT-3′). Following gel electrophoresis, gel extraction, and quantification, the DNA libraries were constructed and sequenced using the Illumina NovaSeq platform (Wuhan MetWare Biotechnology, Wuhan, China). Raw 16S rRNA sequencing data were processed using QIIME (version 1.9.1). Taxonomic classification of operational taxonomic units (OTUs) was performed using the RDP Classifier software (version 2.2) against the 16S rRNA gene database. Alpha (α) diversity indices were calculated using QIIME, while beta (β) diversity was assessed through principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic mean (UPGMA) clustering, utilizing both QIIME (version 1.9.1) and R software (version 2.15.3). Differences in microbial composition among groups were analyzed using Metastats and linear discriminant analysis effect size (LEfSe).

2.4.5 Metabolomics analysis of feces. Fecal samples (n = 6 per group) were extracted with 70% methanol and incubated at −20 °C for 30 min. The extracts were centrifuged at 12 000 rpm for 10 min at 4 °C. The resulting supernatants were transferred to new 1.5 mL centrifuge tubes and centrifuged again under the same conditions. The final supernatants were subjected to metabolomic analysis using an LC-MS/MS system (HPLC: Shim-pack UFLC SHIMADZU CBM30A; MS/MS: QTRAP® 6500+ tandem mass spectrometer), following previously described methods.²¹ Briefly, the ion transport capillary temperature was set to 450 °C, with curtain gas, ion source gas 1, and ion source gas 2 maintained at 25 psi, 55 psi and 60 psi, respectively. The UPLC mobile phase consisted of solvent A (water with 0.1% formic acid) and solvent B (acetonitrile with 0.1% formic acid). The optimized gradient elution program was as follows: 0 min, 5% B; 11 min, 90% B; 12 min, 90% B; 12.1 min, 5% B; 14 min, 5% B. The flow rate was set at 0.4 mL min⁻¹, with an injection volume of 2 μL, and a column temperature of 40 °C. All metabolomic analyses were conducted in accordance with standard operating procedures provided by Wuhan MetWare Biotechnology (Wuhan, China). Raw data were processed on the Majorbio Cloud Platform (https://cloud.majorbio.com). Filtered data were used to generate orthogonal partial least squares discriminant analysis (OPLS-DA) score plots and volcano plots to visualize metabolic differences. Venn diagrams and heatmaps were created using OmicStudio tools (https://www.omicstudio.cn/tool). KEGG pathway enrichment analysis was performed using the MetaboAnalyst 6.0 platform (https://www.metaboanalyst.ca/).

2.5 Statistical analysis

All graphs were generated using GraphPad Prism (version 8.0), OmicStudio tools, MetaboAnalyst 6.0, R software (version 2.15.3), and QIIME software (version 1.9.1). Statistical analyses were performed using one-way ANOVA in SPSS (version 18.0), followed by Duncan's or LSD post hoc tests to assess differences among groups. Differences were considered statistically significant at p < 0.05 or p < 0.01. Data are expressed as mean ± standard deviation (SD).

3 Results

3.1 Optimization of eucalyptus leaf extracts

Three extraction methods were evaluated to obtain Eucalyptus leaf polyphenol extracts with optimal extraction efficiency and total polyphenol content. As shown in Table 1, the LCPTE method yielded the highest extraction efficiency, followed by UWE and then SE. Among the species tested, Eucalyptus grandis × E. urophylla consistently produced higher extraction yields across all methods compared to the other two species (p < 0.05). Regarding total polyphenol content, both LCPTE and UWE significantly outperformed SE (p < 0.05). Notably, E. grandis × E. urophylla exhibited the highest total polyphenol concentration (300.95 ± 16.37 mg g⁻¹), while E. tereticornis showed the lowest (223.26 ± 14.18 mg g⁻¹) (p < 0.05). These findings indicate that LCPTE is the most effective method in terms of both yield and polyphenol concentration.

Table 1 Extraction efficiency and total polyphenols content from three sources of eucalyptus leaves by three extraction methods

Botanical name	Extraction methods	Extraction efficiency (%)	Total polyphenols content (mg g^−1)
Different letters among data for extraction efficiency and total content of eucalyptus leaf polyphenols by three extraction methods indicate values that were significantly different (p < 0.05).
E. grandis × E. urophylla	SE	25.86 ± 1.33a	241.80 ± 11.22b
	UWE	26.48 ± 0.39a	272.38 ± 15.58a
	LCPTE	27.01 ± 2.58a	300.95 ± 16.36a
E. tereticornis	SE	23.21 ± 2.01b	223.26 ± 14.18b
	UWE	25.35 ± 0.86ab	251.97 ± 8.24a
	LCPTE	26.46 ± 1.35a	266.93 ± 8.89a
E. urophylla	SE	22.61 ± 1.05a	229.93 ± 23.01b
	UWE	24.10 ± 1.83a	272.38 ± 17.35a
	LCPTE	25.15 ± 1.87a	290.06 ± 9.20a

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To further identify the extract with the strongest antioxidant capacity, hydroxyl radical (˙OH) scavenging activity and ABTS⁺ radical scavenging ability were assessed. As shown in SI Fig. S1A–C, antioxidant activity followed the same trend across all methods: LCPTE > UWE > SE. SI Fig. S1D shows that LCPTE-extracted samples exhibited the lowest IC₅₀ values, indicating stronger antioxidant capacity, while SE extracts had the highest IC₅₀ values. Specifically, EPEGU demonstrated the most potent ˙OH scavenging activity, with the lowest IC₅₀ value of 0.159 ± 0.004 mg mL⁻¹. ABTS⁺ scavenging assays confirmed these results. As shown in SI Fig. S2A–C, all samples showed concentration-dependent activity, again in the order LCPTE > UWE > SE. EPEGU by LCPTE displayed the lowest ABTS⁺ IC₅₀ value (0.178 ± 0.01 mg mL⁻¹), further supporting its superior antioxidant potential (SI Fig. S2D). Based on these results, EPEGU extracted via LCPTE was selected for subsequent investigations.

3.2 Anti-inflammatory activity of EPEGU and identification of its anti-inflammatory components

3.2.1 Effect of EPEGU on anti-inflammatory activity in LPS-induced RAW264.7 macrophages. RAW264.7 macrophages were employed as an in vitro model to evaluate the anti-inflammatory activity of EPEGU. The MTT assay revealed that EPEGU significantly reduced cell viability at concentrations of 200 and 400 μg mL⁻¹ compared to the control group (p < 0.05), while no significant cytotoxicity was observed at 12.5–100 μg mL⁻¹ (p > 0.05) (Fig. 1A). Based on these results, concentrations of 25, 50, and 100 μg mL⁻¹ were selected for subsequent experiments. As shown in Fig. 1B, LPS stimulation markedly elevated NO production (14.43 ± 2.57 μmol L⁻¹) compared to the control (1.27 ± 0.78 μmol L⁻¹), confirming successful inflammation induction. Treatment with DXM significantly suppressed NO levels (2.52 ± 0.81 μmol L⁻¹; p < 0.01). EPEGU inhibited LPS-induced NO production in a dose-dependent manner, achieving a maximum inhibition of 70.55% at 100 μg mL⁻¹ (p < 0.01). Pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 were also quantified to assess the anti-inflammatory effects of EPEGU (Fig. 1C–E). LPS markedly increased TNF-α levels (148.43 ± 13.35 pg mL⁻¹) compared to the control (14.40 ± 2.64 pg mL⁻¹; p < 0.01). EPEGU significantly reduced TNF-α expression by 15.96% and 51.53% at 50 and 100 μg mL⁻¹, respectively. Similar trends were observed for IL-1β and IL-6, both of which were significantly decreased by EPEGU in a dose-dependent manner (p < 0.01). These findings demonstrate that EPEGU exhibits potent in vitro anti-inflammatory activity by inhibiting NO production and suppressing pro-inflammatory cytokine release in LPS-stimulated RAW264.7 macrophages.

Fig. 1 Effect of EPEGU on inflammatory injury in LPS-stimulated macrophages. A, Cell viability of macrophages exposed to EPEGU; B, NO release by LPS-stimulated RAW264.7 macrophages; C, TNF-α release by LPS-stimulated RAW264.7 macrophages; D, IL-1β release by LPS-stimulated RAW264.7 macrophages; E, IL-6 release by LPS-stimulated RAW264.7 macrophages. LPS, lipopolysaccharide; DXM, dexamethasone; EPEGU, eucalyptus leaf polyphenols extracted from E. grandis × E. urophylla. Control group vs. LPS group: $p < 0.05, $$p < 0.01; sample group vs. LPS group: *p < 0.05, **p < 0.01.

3.2.2 Bioactivity-guided isolation of anti-inflammatory components from EPEGU. To identify the key anti-inflammatory components of EPEGU, bioactivity-guided fractionation was performed using an LPS-stimulated macrophage model. As shown in Fig. 2A, all three isolated fractions (12.5–100 μg mL⁻¹) maintained cell viability above 90%, with no significant cytotoxicity compared to the control (p > 0.05). As illustrated in Fig. 2B and C, all fractions exhibited dose-dependent anti-inflammatory activity, with fraction 2 displaying the strongest inhibitory effects on NO and TNF-α production. At 100 μg mL⁻¹, fraction 2 achieved maximal inhibition rates of 57.62% and 59.14% for NO and TNF-α, respectively. HPLC analysis of fraction 2 (Fig. 2D) revealed a predominant peak (peak 1) at 12.784 min, suggesting a major bioactive compound. This peak was isolated via preparative HPLC, and its mass spectrum displayed a [M − H]⁻ ion at m/z 1567.1416 (Fig. 2E), corresponding to a molecular formula of C₆₈H₄₈O₄₄. Based on literature comparisons^22–24 and matching retention time with an authentic standard, the compound was identified as oenothein B (OEB). The isolated OEB was subsequently used for further functional and mechanistic studies.

Fig. 2 Bioactivity-guided isolation of anti-inflammatory components from EPEGU. A, Cell viability of macrophages exposed to three fractions from EPEGU; B, NO release by LPS-stimulated RAW264.7 macrophages; C, TNF-α release by LPS-stimulated RAW264.7 macrophages; D, HPLC diagram of fraction 2 from EPEGU; E, mass spectrum diagram of purified peak 1 in fraction 2. LPS, lipopolysaccharide; EPEGU, eucalyptus leaf polyphenols extracted from E. grandis × E. urophylla. Fractions 1, 2, and 3 were isolated from EPEGU, respectively. Control group vs. LPS group: $p < 0.05, $$p < 0.01; sample group vs. LPS group: *p < 0.05, **p < 0.01.

3.3 Anti-inflammatory activity of OEB from EPEGU

The anti-inflammatory effects of OEB were assessed using an LPS-induced RAW264.7 macrophage model. As shown in Fig. 3A, OEB at concentrations of 12.5–50 μg mL⁻¹ did not exhibit significant cytotoxicity compared to the control group (p > 0.05), and these concentrations were therefore selected for subsequent experiments. As presented in Fig. 3B, OEB significantly and dose-dependently inhibited NO production in LPS-stimulated macrophages. At 50 μg mL⁻¹, OEB reduced NO levels to 2.69 ± 1.62 μmol L⁻¹—an 82.01% decrease compared to the LPS group (14.96 ± 2.20 μmol L⁻¹; p < 0.01)—and showed no significant difference from the control group (1.94 ± 1.12 μmol L⁻¹; p > 0.05). Fig. 3C–E demonstrates that OEB also markedly suppressed the secretion of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 in a dose-dependent manner. At 50 μg mL⁻¹, the maximum inhibition rates for TNF-α, IL-1β, and IL-6 were 76.15%, 80.16%, and 70.65%, respectively (p < 0.01). To confirm these findings at the transcriptional level, the mRNA expression of iNOS, TNF-α, IL-1β, and IL-6 was measured via RT-qPCR. As shown in Fig. 3F–I, LPS significantly upregulated the expression of all four genes compared to the control (p < 0.05), confirming successful induction of inflammation. OEB treatment led to a significant, dose-dependent reduction in the mRNA levels of iNOS, TNF-α, IL-1β, and IL-6 (p < 0.05). These results collectively demonstrate that OEB exerts potent anti-inflammatory effects in LPS-induced RAW264.7 macrophages by inhibiting both the secretion and gene expression of key inflammatory mediators.

Fig. 3 Effect of OEB on inflammatory injury in LPS-stimulated macrophages. A, Cell viability of macrophages exposed to OEB; B, NO release by LPS-stimulated RAW264.7 macrophages; C, TNF-α release by LPS-stimulated RAW264.7 macrophages; D, IL-1β release by LPS-stimulated RAW264.7 macrophages; E, IL-6 release by LPS-stimulated RAW264.7 macrophages; F, the relative mRNA levels of iNOS; G, the relative mRNA levels of TNF-α; H, the relative mRNA levels of IL-1β; I, the relative mRNA levels of IL-6. LPS, lipopolysaccharide; DXM, dexamethasone; OEB, oenothein B. Control group vs. LPS group: $p < 0.05, $$p < 0.01; sample group vs. LPS group: *p < 0.05, **p < 0.01.

3.4 The amelioration effect of OEB on DSS-induced ulcerative colitis

3.4.1 Effect of OEB on the symptoms of DSS-induced ulcerative colitis. To evaluate the anti-inflammatory effects of OEB in vivo, a DSS-induced UC model was established (Fig. 4A). As shown in Fig. 4B and C, mice in the model group exhibited a significant reduction in body weight and a notable increase in spleen index compared with the control group, confirming the successful induction of colitis (p < 0.05). Treatment with OEB significantly attenuated these changes, effectively restoring both body weight and spleen index in colitic mice (p < 0.05). Furthermore, the DSS-induced shortening of colon length was markedly reversed following OEB administration (p < 0.05, Fig. 4E), which is further illustrated by representative images of colon morphology across experimental groups (Fig. 4D). As a key indicator of disease severity in UC, the DAI scores were significantly elevated in the DSS group (p < 0.05). However, OEB treatment resulted in a dose-dependent reduction in DAI scores, indicating progressive symptom relief (p < 0.05, Fig. 4F). Histopathological analysis of the colon was conducted to further assess the therapeutic effects of OEB on DSS-induced colitis. As illustrated in Fig. 4G, colonic tissues from the DSS-treated group exhibited severe mucosal damage, extensive inflammatory cell infiltration, neutrophil accumulation, crypt architectural disruption, and goblet cell loss compared to the control group. These pathological changes were substantially alleviated in the OEB-treated groups, as reflected by corresponding reductions in histological damage scores (Fig. 4H), which corroborated the micrographic findings. Notably, although some structural abnormalities persisted in OEB-treated mice, the overall epithelial architecture showed a clear trend toward normalization, particularly in animals receiving higher doses of OEB. Collectively, these findings demonstrate that OEB exerts a significant protective effect against DSS-induced colitis, as evidenced by improvements in clinical symptoms, colon morphology, and histopathological outcomes.

Fig. 4 Effect of OEB on the symptoms of DSS-induced ulcerative colitis in mice. A, Experiment design for the administration of OEB and DSS in mice; B, body weight changes; C, spleen index; D, representative images of colon length; E, colon length; F, DAI scores during DSS treatment; G, representative histological micrographs of the colon tissues; H, histological score of the colon. L-OEB, low dose of oenothein B; H-OEB, high dose of oenothein B. Control group vs. model group: $p < 0.05, $$p < 0.01; sample group vs. model group: *p < 0.05, **p < 0.01.

3.4.2 Effect of OEB on anti-inflammatory and antioxidant activity of colon tissues. Inflammation and oxidative stress are key contributors to intestinal barrier dysfunction and the progression of UC.²⁵ To further investigate OEB's protective effects, inflammatory and oxidative markers were assessed in the colons of DSS-induced UC mice. As shown in Fig. 5A–C, DSS treatment significantly elevated colonic levels of TNF-α, IL-1β, and IL-6 compared to the control group (p < 0.05). OEB administration significantly reduced these pro-inflammatory cytokines in a dose-dependent manner, restoring them toward baseline levels (p < 0.05), indicating a strong anti-inflammatory effect. In parallel, oxidative stress was evident in the DSS group, as shown by markedly reduced activities of antioxidant enzymes—SOD, GPx, and CAT—alongside elevated levels of MDA, a lipid peroxidation marker (p < 0.05; Fig. 5D–G). OEB treatment effectively reversed these changes, enhancing SOD, GPx, and CAT activity while reducing MDA content. Higher doses of OEB showed more pronounced antioxidant effects. Collectively, these results demonstrate that OEB protects the colon from inflammation and oxidative stress in UC by modulating pro-inflammatory mediators and restoring antioxidant defense systems.

Fig. 5 Effect of OEB on anti-inflammatory and antioxidant activity of the colon. A, TNF-α level; B, IL-1β level; C, IL-6 level; D, SOD activity; E, GPx activity; F, CAT activity; G, MDA content. L-OEB, low dose of oenothein B; H-OEB, high dose of oenothein B. Control group vs. model group: $p < 0.05, $$p < 0.01; sample group vs. model group: *p < 0.05, **p < 0.01.

3.4.3 OEB modulated the gut microbiota. The structure of the gut microbiota plays a critical role in the pathogenesis of DSS-induced inflammatory bowel disease and is closely associated with UC.⁵ Given the superior efficacy of high-dose OEB in ameliorating UC symptoms, we focused on this group to evaluate its impact on gut microbial composition. Rarefaction curve analysis confirmed that the sequencing depth adequately captured the microbial diversity and identified the majority of phylotypes present (Fig. 6A), ensuring the reliability of the data. α-Diversity analysis revealed no significant changes in overall microbial richness or diversity following OEB treatment. As shown in the Venn diagram (Fig. 6B), the numbers of unique OUTs in the control, DSS, and OEB-treated groups were 247, 233, and 348, respectively, indicating that OEB may enrich specific microbial populations. PCoA and UPGMA clustering further demonstrated distinct microbial community structures between groups, with clear separation between OEB-treated and DSS-only mice (Fig. 6C and D). These results suggest that OEB modulates the gut microbiota composition in UC mice, potentially contributing to its therapeutic effects.

Fig. 6 Effect of OEB on modulation of gut microbiota in the colon of UC mice. A, Rarefaction curve of all samples; B, Venn diagram illustrating the common and unique OTU or taxon between groups; C, PCoA showing the clustering of different samples; D, UPGMA tree showing similarities between different samples; E, average relative abundance of colonic microbiota at the phylum level; F, average relative abundance of colonic microbiota at the genus level; G, linear discriminant analysis (LDA) effect size (LefSe) analysis among three groups. OEB, oenothein B; DSS, dextran sulfate sodium.

To further characterize the effects of OEB on gut microbiota, taxonomic profiles at the phylum and genus levels were analyzed. At the phylum level, Firmicutes, Verrucomicrobiota, Bacteroidetes, and Proteobacteria were predominant across all groups (Fig. 6E). Compared with the control group, DSS treatment significantly increased the relative abundance of Bacteroidetes, Proteobacteria, Deferribacteres, Desulfobacterota, and Campilobacterota, while reduced Firmicutes and Actinobacteriota levels (p < 0.05). OEB treatment reversed these alterations by elevating Firmicutes abundance, increasing the Firmicutes/Bacteroidetes (F/B) ratio, and suppressing Proteobacteria, Deferribacteres, Desulfobacterota, and Campilobacterota (p < 0.05). At the genus level, DSS exposure led to significant increases in Bacteroides, Escherichia–Shigella, Odoribacter, Vibrio, Prevotella, Agathobacter, Collinsella, Utterella, and Ruegeria (p < 0.05; Fig. 6F). In contrast, OEB supplementation mitigated these changes by decreasing the abundance of Bacteroides, Escherichia–Shigella, and Mucispirillum, while enriching beneficial genera such as Streptococcus and [Eubacterium]_fissicatena_group (p < 0.05). Moreover, the levels of Akkermansia, Lactobacillus, and Ruminococcus, which were reduced in DSS-treated mice, were at least partially restored by OEB treatment (p > 0.05). These results suggest that OEB alleviates dysbiosis by restoring the balance and structural integrity of the gut microbiota.

LEfSe analysis further identified specific microbial biomarkers across groups (Fig. 6G). The control group was enriched in taxa such as p_Firmicutes, o_Lactobacillales, f_Lactobacillaceae, g_Lactobacillus, o_Corynebacteriales, f_Corynebacteriaceae, g_Corynebacterium, and s_Corynebacterium_stationis. In the DSS group, 19 discriminatory taxa were identified, with p_Bacteroidota, p_Proteobacteria, g_Bacteroides, f_Enterobacteriaceae, g_Escherichia–Shigella, s_Escherichia_coli, and g_Schlegelella showing LDA scores above 4.0, indicating strong associations with colitis. In contrast, the OEB-treated group exhibited higher relative abundances of f_Muribaculaceae, g_Dubosiella, and g_Eubacterium_fissicatena_group. Overall, these results demonstrate that DSS-induced colitis significantly disrupts gut microbial composition, while OEB supplementation effectively mitigates dysbiosis by reducing harmful bacteria and promoting beneficial microbial taxa.

3.4.4 Effect of OEB on fecal metabolomics. The effects of OEB on fecal metabolites in UC mice were evaluated using untargeted metabolomics. Total ion chromatograms in both positive and negative ion modes confirmed the stability and reliability of the analytical system (SI Fig. S3A and B). Hierarchical clustering analysis revealed distinct metabolite profiles among the control, DSS, and OEB groups (SI Fig. S3C). As shown in Fig. 7A, OPLS-DA score plots demonstrated clear separations between the control and DSS groups, and between the DSS and OEB groups, indicating significant metabolic alterations induced by DSS and their partial reversal following OEB treatment. Compared to the control group, 127 metabolites were upregulated and 68 downregulated in the DSS group. In contrast, the OEB group exhibited 56 downregulated and 10 upregulated metabolites relative to the DSS group. Corresponding volcano plots are shown in Fig. 7B. A Venn diagram (Fig. 7C) identified 31 overlapping differential metabolites shared between the “control vs. DSS” and “DSS vs. OEB” comparisons. Among these, 17 metabolites (15 upregulated and 2 downregulated in the DSS group) were restored toward control levels following OEB administration (Fig. 7D; SI Table S1). To explore the biological relevance of these changes, KEGG enrichment analysis was performed using MetaboAnalyst 6.0 on 17 significantly restored metabolites. As shown in Fig. 7E, OEB treatment notably affected pathways associated with arachidonic acid metabolism. Additionally, the OEB group showed restored levels of tauroursodeoxycholic acid, hyocholic acid, and hyodeoxycholic acid, which were decreased in DSS-treated mice, suggesting a regulatory role of OEB in bile acid metabolism.

Fig. 7 Effect of OEB on metabolism in the colon of UC mice. A, OPLS-DA score plots between control and DSS groups, and DSS and OEB groups; B, volcano plots of differentially altered metabolites between control and model groups, and DSS and OEB groups; C, Venn diagram of the altered metabolites between “control group vs. DSS group” and “DSS group vs. OEB group”; D, the shared metabolites between “control group vs. DSS group” and “DSS group vs. OEB group”; E, KEGG enrichment pathways for the shared 17 metabolites. OEB, oenothein B; DSS, dextran sulfate sodium.

3.4.5 Correlation of physiological indexes and gut microbiota and metabolites. Spearman correlation analysis was conducted to investigate associations among physiological parameters, gut microbiota, and fecal metabolites in UC mice (Fig. 8). Proteobacteria, Bacteroides, and Escherichia–Shigella were positively correlated with pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) and MDA, while negatively correlated with beneficial bacteria (Firmicutes, Akkermansia, Lactobacillus, and Ruminococcus) and antioxidant enzymes (SOD, CAT, GPx). Additionally, these pathogenic taxa were negatively associated with metabolites involved in arachidonic acid (AA) metabolism—such as PGF2α, TXB2, 5,6-EET, and 8,9-EET—and positively correlated with reductions in bile acid metabolites including tauroursodeoxycholic acid, hyocholic acid, and hyodeoxycholic acid. These patterns suggest that DSS-induced colitis disrupts the interplay among microbial composition, host redox balance, inflammation, and metabolic pathways. In contrast, the relative enrichment of Firmicutes, Akkermansia, Lactobacillus, and Ruminococcus in the OEB-treated group was positively correlated with antioxidant enzyme levels and negatively correlated with MDA and inflammatory cytokines. These beneficial bacteria also showed positive correlations with bile acid metabolites and negative correlations with AA pathway intermediates elevated during inflammation. Together, these results suggest that OEB supplementation alleviates UC symptoms by restoring microbial balance, enhancing antioxidant and anti-inflammatory responses, and modulating metabolite profiles. OEB effectively mitigates DSS-induced disruptions in physiological, microbial, and metabolic homeostasis in UC mice.

Fig. 8 Correlation analysis among physiological indexes and gut microbiota and metabolites was performed using the Spearman correlation test. The darker the color the larger the circle size and stronger the correlation. Positive correlations are shown in red, and negative correlations are shown in blue. *p < 0.05, **p < 0.01.

4 Discussion

Nonvolatile constituents of Eucalyptus leaves have been reported to exhibit various bioactivities, including antioxidant, antitumor, antibacterial, and antifungal effects.^16,26,27 In this study, polyphenols extracted from EPEGU using LCPTE were obtained, yielding a high total polyphenol content with strong antioxidant activity. Notably, antioxidant and anti-inflammatory properties of natural polyphenols are often interrelated.²⁸ Traditionally, Eucalyptus has been used to treat inflammatory conditions, and recent studies suggest that its polyphenols contribute significantly to these effects.^29,30 However, the anti-inflammatory potential of Eucalyptus leaf polyphenol extracts remains underexplored. To address this, we preliminarily assessed the anti-inflammatory activity of EPEGU using RAW264.7 macrophages, which are central to initiating and sustaining the inflammatory response in UC. As expected, EPEGU significantly and dose-dependently suppressed NO production and the release of pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) in LPS-stimulated macrophages. These findings suggest that EPEGU holds promise as a natural anti-inflammatory agent. However, EPEGU comprises a complex mixture of phenolics, and the specific compounds responsible for its activity remain unclear. To further clarify the active components, OEB—a unique hydrolyzable tannin—was isolated and identified as a major phenolic compound in E. grandis × E. urophylla leaves. OEB exhibited stronger anti-inflammatory activity than the crude EPEGU extract, indicating that it may be a key contributor to the extract's bioactivity. OEB also significantly downregulated mRNA expression of iNOS, TNF-α, IL-1β, and IL-6 in LPS-stimulated macrophages. Previous studies indicated that OEB from Onagraceae species inhibits TLR/NF-κB-dependent inducible nitric oxide and cytokine synthesis, an anti-inflammatory activity that relied on its intact molecular structure, thereby highlighting its potential as a functional ingredient for dietary use.³¹ While OEB's in vitro anti-inflammatory effects are well-documented, its in vivo efficacy remains less understood. Therefore, investigating OEB's function in vivo is essential to fully elucidate its therapeutic potential. In summary, OEB derived from Eucalyptus leaves demonstrates potent in vitro anti-inflammatory activity and represents a promising candidate for further development.

UC is a chronic inflammatory disease with a multifactorial etiology involving genetic, environmental, and dietary factors.³² Plant-derived phenolic compounds have been reported to alleviate UC symptoms by reducing colonic inflammation and modulating gut microbiota dysbiosis.^33,34 Although emerging evidence highlights the therapeutic potential of Eucalyptus-derived polyphenols in inflammatory bowel diseases, including UC,³⁵ their efficacy and underlying mechanisms remain poorly understood due to limited in vivo research. In this study, we identified OEB as a key anti-inflammatory component from Eucalyptus polyphenols. Notably, no prior studies have reported the effects of OEB in a DSS-induced UC mouse model. Our findings demonstrate that OEB significantly alleviated general UC symptoms, including weight loss, splenomegaly, colon shortening, and bloody stools. Histopathological analysis further confirmed that OEB mitigated colonic damage, including mucosal erosion, crypt loss, goblet cell depletion, and inflammatory cell infiltration. These results are consistent with previous reports showing the beneficial effects of polyphenols on colitis symptoms, such as body weight, colon length, and histological integrity.^7,36 Given that oxidative stress and inflammation are central to UC pathogenesis,³⁷ the antioxidant and anti-inflammatory properties of OEB are particularly relevant. Excessive production of reactive oxygen species (ROS) impairs the intestinal barrier and promotes inflammation, exacerbating disease progression. Mounting evidence suggests that reducing oxidative stress and inflammation can ameliorate UC symptoms.³⁸ Our data show that OEB enhances antioxidant defenses and suppresses inflammatory responses in the colon. These effects may be attributed to OEB's polyhydroxylated structure, previously reported to contribute to its bioactivity,³⁹ which supported the potential use of OEB as a natural anti-inflammatory agent. In addition, these results hinted that although the leaves of E. grandis × E. urophylla are not conventionally consumed as food, the isolated compound OEB exhibited strong potential as a functional ingredient for nutraceutical or dietary supplement applications in inflammatory bowel diseases. In summary, OEB derived from Eucalyptus leaves effectively alleviates DSS-induced UC in mice, likely by reducing oxidative stress and inflammation. These findings support OEB as a promising natural compound for further investigation in UC therapy.

Accumulating evidence indicates that gut microbiota dysbiosis plays a critical role in the pathogenesis of UC, characterized by a reduction in beneficial microbes and an increase in opportunistic and pathogenic bacteria.^40,41 Notably, Firmicutes abundance is negatively correlated with UC incidence. A higher Firmicutes level has been shown to reduce intestinal sensitivity to inflammation, potentially minimizing organ damage caused by endotoxin leakage through a compromised gut barrier.⁴² In contrast, Bacteroidetes abundance is often elevated in UC, and its enrichment has been associated with pro-inflammatory effects.⁴³ A reduced Firmicutes/Bacteroidetes (F/B) ratio is a common feature in both UC mouse models and human IBD patients, reflecting gut barrier dysfunction and heightened inflammatory response.^44,45 In this study, OEB treatment significantly increased Firmicutes abundance and restored the F/B ratio in DSS-induced UC mice, suggesting its potential to protect the intestinal barrier and suppress colonic inflammation by correcting microbial imbalances. Additionally, OEB reduced the relative abundance of several phyla elevated in the DSS group, including Proteobacteria, Deferribacteres, Desulfobacterota, and Campilobacterota, which were previously linked to UC pathology.^46,47Proteobacteria comprises numerous pathogenic genera such as Escherichia, Salmonella, and Vibrio, whose expansion is a hallmark of gut dysbiosis and a known driver of IBD.⁴⁶ Similarly, Deferribacteres, Desulfobacterota, and Campilobacterota are pro-inflammatory taxa associated with increased production of inflammatory mediators and exacerbation of UC symptoms.⁴⁸ Collectively, these findings suggest that OEB alleviates DSS-induced gut microbiota dysbiosis at the phylum level by promoting the growth of anti-inflammatory taxa like Firmicutes while suppressing inflammation-associated phyla. This microbial modulation may contribute to its protective effects against UC.

Increased abundances of Bacteroides, Escherichia–Shigella, Odoribacter, Vibrio, Prevotella, Agathobacter, Collinsella, and Utterella Ruegeria were observed at the genus level in DSS-induced UC mice, consistent with previous reports.⁴⁹ Notably, Bacteroides is known to secrete a 20 kDa zinc-dependent metalloprotease toxin that exacerbates colonic inflammation.⁵⁰ Elevated Bacteroides levels have been detected in both DSS-induced colitis models and UC patients, suggesting its potential as a biomarker for disease onset and progression.⁵¹Escherichia–Shigella, Odoribacter, and Vibrio are recognized pathogens that contribute to intestinal inflammation and microbial dysbiosis. Although the precise roles of Prevotella, Agathobacter, Collinsella, and Utterella Ruegeria in UC remain unclear, Prevotella has been associated with pro-inflammatory microbiota and may promote disease severity in certain microbial contexts.⁵² OEB treatment significantly reduced the abundance of Bacteroides, Escherichia–Shigella, and Mucispirillum, while increased levels of Streptococcus and [Eubacterium]_fissicatena_group, in line with previous findings.⁵³Mucispirillum, a member of the phylum Deferribacteres, has been proposed as a microbial indicator of DSS-induced colitis.⁵⁴ Importantly, OEB also elevated the relative abundance of Akkermansia, Lactobacillus, and Ruminococcus—genera typically regarded as beneficial due to their roles in modulating inflammation, producing short-chain fatty acids, and maintaining gut barrier integrity.⁵⁵ Further support came from LEfSe analysis, which revealed that harmful taxa such as p_Bacteroidota, p_Proteobacteria, g_Bacteroides, f_Enterobacteriaceae, g_Escherichia–Shigella, s_Escherichia coli, and g_Schlegelella were enriched in the DSS group. In contrast, beneficial taxa including f_Muribaculaceae, g_Dubosiella, and g_Eubacterium_fissicatena_group were more abundant in the OEB-treated group, reflecting a favorable microbial shift. Collectively, these findings confirm that DSS-induced UC results in pronounced gut microbiota dysbiosis, which can be partially reversed by OEB treatment through the suppression of pathogenic bacteria and enrichment of beneficial taxa.

Colitis-induced dysbiosis of the intestinal microbiota can lead to metabolic disturbances, as evidenced by significant alterations in metabolites observed in both colitis mouse models and patients.^56,57 In this study, we found that OEB treatment notably modulated AA metabolism, which plays a key role in inflammatory processes. AA, an ω-6 polyunsaturated fatty acid primarily stored in membrane phospholipids under physiological conditions, is rapidly converted into various bioactive metabolites—such as prostaglandins (PGs), epoxyeicosatrienoic acids (EETs), and thromboxanes (TXs)—in response to external stimuli.⁵⁸ These metabolites, including PGF2α, TXB2, 5,6-EET, and 8,9-EET, are recognized as proinflammatory mediators and have been positively correlated with the severity of inflammation in UC mouse models.⁵⁹ Disruption of AA metabolism has been implicated in the exacerbation of UC symptoms.⁶⁰ Consistent with previous reports, our results showed significant increases in PGF2α, TXB2, 5,6-EET, and 8,9-EET in the DSS-induced colitis group, indicating marked perturbation of AA metabolism. Notably, OEB treatment reversed these alterations. Similar findings have been reported in studies where natural polyphenols ameliorated UC by restoring AA metabolic balance and reducing the levels of these proinflammatory metabolites.^61,62 Such interventions are believed to maintain microbial homeostasis, reinforce intestinal barrier integrity, and suppress the release of inflammatory mediators, thereby mitigating DSS-induced colonic inflammation.⁶³ Our data further demonstrated that OEB treatment improved the gut microbiota composition, characterized by an increase in Firmicutes and a reduction in Bacteroidetes and Proteobacteria. These microbial shifts were associated with decreased expression of proinflammatory cytokines (TNF-α, IL-1β, IL-6) and amelioration of colonic inflammation. Additionally, normalization of AA metabolism and a corresponding decrease in proinflammatory metabolites contributed to symptom relief in UC. Collectively, these results suggest that metabolic disturbances in UC are downstream consequences of microbiota dysbiosis. OEB effectively reversed these changes, supporting its therapeutic potential. Moreover, DSS-induced colitis disrupted bile acid metabolism, as evidenced by significantly reduced levels of tauroursodeoxycholic acid, hyocholic acid, and hododeoxycholic acid compared with controls. Previous studies have similarly reported that several bile acids—including taurocholic acid, taurochenodeoxycholic acid, chenodeoxycholic acid, and ursodeoxycholic acid—are significantly reduced in UC mouse models compared to healthy controls.⁶⁴ In the present study, OEB treatment effectively restored these bile acids in DSS-induced UC mice, suggesting a modulatory effect on bile acid metabolism. This restoration may be partly attributed to the influence of OEB on gut microbiota composition, particularly the increased abundance of Firmicutes and reduced levels of Proteobacteria. Wu et al. demonstrated that suppression of Proteobacteria, especially Escherichia–Shigella, facilitates the recovery of microbial homeostasis and enhances bile acid biosynthesis, notably of taurochenodeoxycholic acid.⁶⁵ Additionally, members of the Firmicutes phylum—particularly Clostridium species—express key enzymes such as bile salt hydrolase (BSH) and 7α-dehydroxylase, which catalyze the conversion of primary bile acids into secondary bile acids.⁶⁶ These secondary bile acids function as signaling molecules that help suppress intestinal inflammation and maintain epithelial barrier integrity via activation of the FXR/TGR5 pathways.⁶⁷ This, in turn, promotes a stable and health-supporting microbial environment. Therefore, the observed improvement in bile acid profiles may result from OEB-mediated microbial modulation. In summary, a balanced gut microbiota supports bile acid metabolism, which in turn contributes to intestinal barrier preservation and inflammation reduction. Our findings suggest that OEB alleviates DSS-induced metabolic disturbances in UC, primarily through the regulation of arachidonic acid and bile acid metabolism.⁶⁸

5 Conclusions

In conclusion, OEB, derived from Eucalyptus grandis × E. urophylla, demonstrated potent anti-inflammatory effects both in vitro and in vivo. Specifically, OEB treatment significantly alleviated DSS-induced ulcerative colitis in mice by suppressing proinflammatory mediators, enhancing antioxidant defenses, and modulating gut microbiota and related colonic metabolites. Given its origin from natural plant polyphenols, OEB may be a promising dietary functional ingredient used in foods or in dietary supplements for the management of inflammatory diseases.

Author contributions

Wei Li: conceptualization, writing – original draft. Xiaoying Zhang: methodology, software. Lu Xu: resources, visualization. Yunjiao Chen: methodology, resources. Yong Cao: project administration, supervision, writing – review & editing. Ziyin Li: supervision, writing – review & editing.

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

The data supporting this study are available within the article.

Supplementary information (SI) is available. See DOI: https://doi.org/10.1039/d5fo03016a.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 82304178), the Shenzhen Science and Technology Program (JCYJ20240813112052067), Dongguan Social Development Science and Technology Project (No. 20231800900292) and the Haday Visionary Science Advancement Fund.

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Footnote

† These authors contributed equally to the work of this article.

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