The antibiotics metronidazole (S17079, purity ≥98%), vancomycin (S17059, 900 mcg/mg), gentamicin (S17024, 590 µ/mg), clindamycin (S63729, purity ≥98.5%), and kanamycin (S17025, 750 µ/mg) were procured from Shanghai Yuanye Bio-Technology Co., Ltd. Colistin (MB1064, ≥19,000 IU/mg) was obtained from Dalian Meilun Biotechnology Co., Ltd., and dexamethasone (ST1254, purity ≥99%) from Shanghai Beyotime Biotechnology Co., Ltd. 6-Gingerol (PU0924-0200, purity ≥98.5%) was purchased from Chengdu Push Bio-Technology Co., Ltd.

C. difficile strain 630 (ATCC BAA-1382) was provided by ATCC. The strain was cultured on Columbia blood agar plates under standard anaerobic conditions at 37°C for 7 days. C. difficile cells were harvested from the culture medium using a sterile loop and resuspended in phosphate-buffered saline (PBS). To isolate C. difficile spores, the suspension was heat-treated at 65°C for 20 min to eliminate vegetative cells. The treated suspension was centrifuged at 3,000 × g, washed 2-3 times with PBS, and the supernatant discarded. The resulting pellet was resuspended in liquid medium and stored at −80°C for future use.

The prepared C. difficile suspension was adjusted to 0.5 McFarland standard using PBS and inoculated into a 96-well plate. For the experimental group, each well received 180 μL of liquid culture medium and 20 μL of C. difficile suspension, while the control group received 180 μL of liquid culture medium and 20 μL of PBS. During incubation, OD600 values were measured every 2 h to monitor bacterial growth dynamics and generate a growth curve.

After constructing the growth curve, working solutions of 6-Gingerol and fidaxomicin were prepared using anaerobic culture medium. The final concentrations of 6-Gingerol were set at 500 μM, 400 μM, 200 μM, 100 μM, 75 μM, 50 μM, 25 μM, 10 μM, and 5 μM. The final concentrations of fidaxomicin were set at 4 μM, 2 μM, 1 μM, 0.5 μM, 0.25 μM, 0.125 μM, 0.0625 μM, 0.03125 μM, 0.015625 μM, and 0.0078125 μM. For each concentration, 180 μL of the prepared working solution was added into individual wells of a 96-well plate, with three replicates per concentration. Then, 20 μL of freshly prepared C. difficile suspension was added to each well. For the blank control group, 180 μL of the corresponding drug solution and 20 μL of PBS were added to evaluate potential interference of the compounds with the OD readings.

OD600 values were measured at specific time points during the logarithmic growth phase to evaluate the effect of 6-Gingerol on C. difficile growth and to determine its minimum inhibitory concentration (MIC) and half-maximal inhibitory concentration (IC50). MIC: The OD600values were modelled using a modified non-linear regression method based on an F-test (GraphPad Prism 9.0) (Lepe et al., 2013). OD600 data (bacterial growth) were adjusted by the Gompertz equation to calculate the MIC and confidence intervals (CIs) directly, and were not based on the inflection point. IC50: Using GraphPad Prism, the “log (inhibitor) vs. response—Variable slope (four parameters)” model was employed to perform dose-response curve fitting. This method conducts regression analysis on the relationship between the logarithm of the inhibitor concentration and the OD600 response, thereby accurately determining the IC50 value of 6-Gingerol and providing a quantitative basis for evaluating its antimicrobial activity.

Specific-pathogen-free (SPF) male C57BL/6 mice, aged 5 weeks and weighing 20 ± 2 g, were obtained from SPF (Beijing) Biotechnology Co., Ltd. (License No. SCXK (Jing) 2019-0010). The mice were housed in an SPF-grade laboratory with controlled temperature (20°C–26°C), humidity (40%–70%), and a 12-h light/dark cycle. Standard rodent feed and water were provided ad libitum. All animal experiments were conducted in accordance with ethical guidelines approved by the Animal Ethics Committee of Beijing Friendship Hospital, Capital Medical University.

After 1 week of acclimatization, 40 mice were weighed and randomly assigned to five groups (n = 8/group): control (CON), model (MOD), fidaxomicin (FID), low-dose 6-Gingerol (GL), and high-dose 6-Gingerol (GH). Randomization was performed using the RAND function in Excel. All groups were maintained under normal conditions.

The experimental protocol is illustrated in Figure 2A. From day −6 to day −3, mice in the CON group received normal drinking water, while those in the MOD, GL, and GH groups were given water containing a combination of antibiotics and dexamethasone (kanamycin: 0.4 mg/mL; vancomycin: 0.045 mg/mL; metronidazole: 0.215 mg/mL; colistin: 850 U/mL; gentamicin: 0.035 mg/mL; dexamethasone: 0.1 mg/mL). From day −3, all mice resumed normal drinking water. On day −1, mice, except those in the CON group, were intraperitoneally injected with 10 mg/kg clindamycin; the CON group received an equivalent volume of saline. On day 0, all mice, except those in the CON group, were orally administered 500 μL of C. difficile spores (10⁵ CFU/mouse); the CON group received an equivalent volume of saline. From day 1 to day 7, drug treatments were administered daily at 9:00 a.m.: the FID group received 30 mg/kg fidaxomicin, the GH group received 100 mg/kg 6-Gingerol, the GL group received 50 mg/kg 6-Gingerol (Alhamoud et al., 2023; Chang and Kuo, 2015; Guo et al., 2022), and the CON and MOD groups received equivalent volumes of saline. The body weight and general condition of all mice were monitored and recorded. On day 8, all mice were euthanized, and colonic tissues were collected for subsequent analyses.

Clinical symptoms of CDAD were assessed based on the criteria outlined in Table 1 (Fachi et al., 2020).

We utilized RT-qPCR to quantify C. difficile burden by detecting the toxin B gene. Total DNA from mouse feces was extracted using the E.Z.N.A.^® Stool DNA Kit (D4015-01, OMEGA), and the DNA was stored at −20°C. Real-time quantitative PCR (RT-qPCR) was performed using a 25 μL reaction mixture containing 12.5 μL Premix Ex Taq TM (RR390, TAKARA), 0.5 μL Rox reference dye II (AK60353A, TAKARA), 2.5 μL forward and reverse primers with TaqMan probe (1927827100, Sangon Biotech), and 2 μL DNA. The assay was run on a 7500 FAST Real-Time PCR System (Thermo Fisher Scientific) with a two-step PCR amplification protocol: initial denaturation at 95°C for 30 s, followed by 40 cycles of 95°C for 3 s and 50°C for 30 s. Primer and probe sequences were: stcdb-f (5′-3′: ATATCA GAG ACT GAT GAG), stcdb-r (5′-3′: TAGCAT ATT CAG AGA ATA TTG T), and stcdb-p (5′-3′: FAM-C TGG AGA ATC TAT ATT TGT AGA AAC TG-BHQ).

Distal colon tissues were collected immediately after euthanasia, rinsed with pre-cooled PBS, and preserved in RNAlater (AM7021, Invitrogen), followed by storage at −20°C. Total RNA was extracted, and quantitative real-time PCR was performed to assess the expression of IL-1β, TNF-α, Occludin, and ZO-1, using GAPDH as the internal reference gene. Total RNA was extracted using Trizol (391107, Ambion) and reverse transcribed to cDNA using a reverse transcription kit (0202010531, LABLEAD). RT-qPCR was performed with a two-step amplification protocol: initial denaturation at 95°C for 5 min, followed by 40 cycles of 95°C for 10 s and 60°C for 30 s. The reaction mixture included 10 μL SYBR Green Master Mix, 1 μL each of forward and reverse primers, 2 μL DNA template, and 6 μL Nuclease-Free Water. Primer sequences used were: IL-1β (F: 5′-3′: TGT​GAA​ATG​CCA​CCT​TTT​GA, R: 5′-3′: GTC​AAA​GGT​TTG​GAA​GCA​G), TNF-α (F: 5′-3′: CTC​CAG​GCG​GTG​CCT​ATG​T, R: 5′-3′: GAA​GAG​CGT​GGT​GGC​CC), Occludin (F: 5′-3′: TAC​TGT​GTG​GTT​GAT​CCC​CAG, R: 5′-3′: GAT​AAT​CAT​GAA​CCC​CAG​GAC), ZO-1 (F: 5′-3′: CCA​CTC​TTC​CAG​AAC​CGA​AAC​CTG, R: 5′-3′: TTT​CAT​GCT​GGG​CCT​AAG​TAT​CCC), GAPDH (F: 5′-3′: GGC​AAG​GTC​ATC​CCA​GAG​CTG, R: 5′-3′: ATC​CAC​GAC​GGA​CAC​ATT​GGG).

Colonic tissues were fixed in 4% paraformaldehyde, paraffin-embedded, sectioned, and stained with hematoxylin and eosin (H&E) for pathological examination. Goblet cell counts were determined using Alcian Blue staining.

For immunohistochemical analysis, sections were placed in citrate antigen retrieval buffer (pH 6.0) for antigen retrieval and blocked with 3% hydrogen peroxide to inhibit endogenous peroxidase activity. Primary antibodies included rabbit anti-MPO (22225-1-AP, Proteintech) and rabbit anti-MUC2 (27675-1-AP, Proteintech). Negative expression was indicated by blue staining, and positive expression by brown staining.

For immunofluorescence analysis, sections were boiled in EDTA/citrate buffer for antigen retrieval and blocked with PBS containing 3% bovine serum albumin (BSA). Primary antibodies were rabbit anti-ZO-1 (21773-1-AP, Proteintech) and rabbit anti-PCNA (10205-2-AP, Proteintech). Secondary antibodies were Anti-rabbit IgG (H + L), F (ab′)2 Fragment (4412S, CST). Nuclei were stained with DAPI (D1306, Invitrogen), which appeared blue, while FITC-conjugated secondary antibodies appeared green. Semi-quantitative analysis of immunofluorescence and immunohistochemistry was performed using HALO software (Indica Labs, United States).

16S rRNA sequencing targeted five regions (V2, V3, V5, V6, V8) through multiplex PCR amplification and sequencing. PCR products were purified, pooled, and sequenced on an Illumina NovaSeq 6000 platform with paired-end 150 bp reads. Negative extraction controls and no-template PCR controls were included throughout the DNA extraction and library preparation processes to monitor for potential contamination. Data were demultiplexed based on PCR and Barcode sequences, trimmed, and processed using FLASH2 (Version 2.2.00) to generate raw tags. Clean tags were obtained through stringent quality filtering, and chimeric sequences were removed using QIIME (Version 2.0) quality control pipelines. Effective tags were used for species annotation and abundance analysis, including alpha diversity for within-group microbial complexity and beta diversity for inter-group compositional differences. Cluster analysis and species composition comparisons were conducted to identify differences among groups, and statistical methods at various taxonomic levels were applied to analyze bacterial community structure.

At the end of the 6-Gingerol treatment, fecal samples from the CON, MOD, and GH groups were subjected to targeted quantitative analysis of short-chain fatty acids using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). This analysis quantified acetate, propionate, isobutyrate, butyrate, valerate, isovalerate, hexanoic acid, and heptanoic acid. Detailed methods are provided in the supplementary materials, including standard curves (Supplementary Figure S5) and total ion chromatograms (TIC) of samples (Supplementary Figure S6).

Statistical analyses were performed using SPSS 26.0 software. Results are expressed as mean ± standard deviation (SD). One-way ANOVA was used to determine statistical significance, and non-parametric Kruskal-Wallis tests were applied where appropriate. Differences were considered statistically significant at P < 0.05.

This study evaluated the inhibitory effects of various concentrations of 6-Gingerol and the positive control drug fidaxomicin on the growth of Clostridium difficile, aiming to determine their minimum inhibitory concentration (MIC) and half-maximal inhibitory concentration (IC₅₀). As shown in Figure 1A. C. difficile exhibited a typical bacterial growth curve from 14 to 28 h, with OD₆₀₀ increasing from approximately 0.1 to around 1.0 and plateauing after 24 h. Since the logarithmic growth phase occurs between 20 and 22 h, the 22-h time point was selected for MIC and IC₅₀ determination to ensure data consistency and comparability.

As the concentration of 6-Gingerol increased, the growth of C. difficile was significantly inhibited, as reflected by a concentration-dependent decline in OD₆₀₀ values (Figures 1B,C). At lower concentrations, bacterial growth was still partially maintained; however, higher concentrations led to a marked reduction in OD₆₀₀, indicating potent antibacterial activity. Using a “log (inhibitor) vs. response–Variable slope (four parameters)” model for curve fitting, the IC₅₀ of 6-Gingerol was calculated to be approximately 61.99 μM. The MIC, determined using a modified non-linear regression method based on the F-test, was approximately 173.3 μM, at which complete inhibition of bacterial growth was observed. In comparison, the positive control fidaxomicin demonstrated significantly stronger antibacterial activity under the same conditions, with an IC₅₀ of 0.1783 μM and an MIC of 0.2700 μM (Figures 1D,E).

In summary, 6-Gingerol exhibited a clear concentration-dependent inhibitory effect on the growth of C. difficile, with complete inhibition achieved at higher concentrations. Although its antibacterial potency was lower than that of fidaxomicin, 6-Gingerol, as a natural bioactive compound, shows promising potential in combating C. difficile infection and lays a solid foundation for further investigation into its antibacterial mechanisms and clinical applications.

Upon establishing the animal model, we monitored the body weight, clinical symptoms, fecal consistency, and mortality of the mice (Figure 2A). Mice in the CON group exhibited a continuous increase in body weight, whereas those in the other groups experienced a rapid decline in body weight on the first day following gavage with C. difficile spores. In the MOD group, body weight continued to decrease until day five, followed by a gradual increase over the next 2 days. During the treatment phase, the GH, GL, and FID groups showed an upward trend in body weight, with the GH group displaying a rate of weight change closer to the CON group. Significant differences in body weight were observed between the GH and GL groups compared to the MOD group from day two to the end of the experiment, with the most pronounced difference on day five (P < 0.001). These findings indicate that 6-Gingerol significantly restored the body weight of CDAD mice (Figure 2B).

Clinical symptoms and fecal consistency serve as direct indicators of CDAD severity. We employed scoring methods to evaluate these parameters, referencing Figure 2D for fecal consistency and Table 1 for clinical symptoms. Throughout the experiment, clinical and fecal parameters in the CON group remained normal. In contrast, the MOD group consistently showed higher scores than the treatment groups. After treatment, all groups exhibited some degree of recovery from CDAD symptoms. By day seven, fecal consistency in the GH group had returned to normal levels (score 1), with significant improvements in clinical status compared to the MOD group. Similarly, the GL group showed notable recovery. These data demonstrate that 6-Gingerol effectively ameliorates clinical symptoms and fecal consistency in CDAD mice.

On the final day of treatment, fecal samples were collected for quantification of C. difficile load. As shown in Figure 2E, the MOD group exhibited a significantly higher C. difficile load than the CON group, confirming successful model establishment. The FID group showed a C. difficile load comparable to the CON group, indicating effective pathogen suppression. Notably, the GH group demonstrated a significantly lower C. difficile load than both the GL and MOD groups, while no significant difference was observed between the GL and MOD groups. These findings indicate that the marked reduction in C. difficile load achieved by high-dose 6-Gingerol treatment played a critical role in mitigating CDAD.

Histopathological examination of H&E-stained colonic samples (Figure 3A) revealed intact and closely packed mucosal epithelial cells with minimal inflammatory infiltration in the CON group. Conversely, the MOD group exhibited extensive inflammatory cell infiltration into the submucosa, epithelial cell shedding, and severe disruption of the intestinal barrier. The FID group showed reduced inflammatory cell infiltration in the lamina propria and tightly arranged mucosal epithelial cells with only minimal shedding. In both 6-Gingerol treatment groups, colonic tissue pathology was less severe than in the MOD group, with the GH group showing significantly reduced inflammatory infiltration. Both low-dose and high-dose 6-Gingerol treatment markedly improved the colonic histopathological condition of CDAD mice, particularly at a dosage of 100 mg/kg/day.

Myeloperoxidase (MPO), secreted by neutrophils, monocytes, and certain macrophages, was analyzed via immunohistochemistry to assess inflammation in colonic tissues (Figures 3B,E). The MOD group exhibited a significant increase in MPO-positive inflammatory cells compared to the CON group, indicating elevated MPO expression in CDAD mice (P < 0.01). 6-Gingerol treatment significantly inhibited MPO expression in CDAD mice (P < 0.05), comparable to the FID group.

RT-qPCR analysis was used to evaluate the expression of the pro-inflammatory cytokines TNF-α and IL-1β in colonic tissues (Figures 3C,D). Post-modeling, the MOD group showed significantly elevated expression of TNF-α and IL-1β. Treatment with 6-Gingerol significantly reduced the expression of these cytokines, with the GH group showing levels closer to the CON group and comparable to the FID group, indicating potent anti-inflammatory effects of 6-Gingerol on CDAD-induced colonic inflammation.

These findings demonstrate that high-dose 6-Gingerol (100 mg/kg/day) is more effective than low-dose (50 mg/kg/day) in alleviating CDAD symptoms, reducing C. difficile load (P < 0.001), and mitigating colonic inflammation. Therefore, subsequent studies focused on the high-dose treatment group.

To investigate changes in intestinal barrier function associated with CDAD, we assessed the number of goblet cells, the expression of proliferating cell nuclear antigen (PCNA), mucin (MUC2), tight junction protein ZO-1, and integral membrane protein Occludin in colonic tissues (Figure 4). Alcian blue staining revealed a significant decrease in goblet cell numbers in the MOD group, which was markedly restored following 6-Gingerol intervention (Figures 4A,E).

Immunofluorescence was employed to detect PCNA and ZO-1 expression, and immunohistochemistry was used for MUC2 expression. The MOD group exhibited significantly reduced PCNA levels compared to the CON group, whereas 6-Gingerol treatment significantly restored PCNA expression (Figures 4C,G). Similarly, MUC2 expression in the MOD group was significantly lower than in the CON group, but it was significantly elevated in the GH treatment group (Figures 4B,F), a finding further corroborated by RT-qPCR at the gene level (Figure 4J). ZO-1 expression followed a similar trend to MUC2, with significant reductions in the MOD group and significant increases in the GH group following 6-Gingerol treatment (Figures 4D,H). RT-qPCR results for ZO-1 were consistent with immunofluorescence findings (Figure 4I). Additionally, Occludin expression was significantly enhanced by 6-Gingerol treatment, as confirmed by RT-qPCR (Figure 4K).

These results indicate that 6-Gingerol significantly ameliorates CDAD-induced intestinal barrier dysfunction. This improvement might be achieved through restoring goblet cell numbers, promoting PCNA and Occludin expression, and enhancing the expression of MUC2 and ZO-1, thereby facilitating intestinal barrier repair and contributing to the therapeutic efficacy against CDAD.

The overuse or inappropriate use of antibiotics disrupts the gut microbiota, compromising its barrier function and facilitating C. difficile colonization. Based on the therapeutic effects observed in our initial results, we further investigated the impact of 6-Gingerol on the gut microbiota to explore its potential mechanisms. Firstly, we analyzed the diversity of the gut microbiota post-6-Gingerol intervention. Alpha diversity, reflecting within-group diversity, was assessed using six key indices: ACE, Chao1, Fisher, Coverage, Simpson, and Observed. ACE and Chao1 indices elucidated species richness within communities. The Fisher index combined richness and evenness for a comprehensive diversity assessment. The Observed index indicated the number of detected species, while the Simpson index measured species diversity, and the Coverage index estimated sample coverage completeness. Post-modeling, gut microbiota richness and diversity significantly declined. 6-Gingerol treatment showed trends towards restoration in the GH group, with indices approaching those of the CON group (Figures 5A,B) (Supplementary Figures S1A, B). All groups exhibited over 99% Coverage, indicating sufficient sequencing depth for accurate community structure representation (Supplementary Figure S1C).

We further evaluated microbial community composition through Beta diversity analysis, employing Jaccard index-based Principal Coordinates Analysis (PCoA), Principal Component Analysis (PCA), and Non-metric Multidimensional Scaling (NMDS). These analyses indicated inter-group similarities or differences. PCoA revealed significant compositional differences between the MOD and CON groups, indicating altered gut microbiota in the MOD group. The GH group showed compositional changes post-6-Gingerol intervention compared to the MOD group. PCA and NMDS results corroborated PCoA findings, underscoring the impact of 6-Gingerol on gut microbiota composition (Figures 5E,F).

Subsequently, we analyzed the composition of gut microbiota at the phylum (Figure 6) and species (Figure 7) levels based on OTU absolute abundance and annotation information. Firmicutes, Proteobacteria, and Bacteroidetes were the dominant phyla. Post-modeling, Firmicutes decreased, while Proteobacteria and Bacteroidetes increased. 6-Gingerol intervention showed a trend towards restoring Proteobacteria proportions to CON group levels. Using random forest algorithms, we identified biomarkers, ranked by Mean Decrease Accuracy (Figure 6B). Random forest and Stamp analyses indicated increased Actinobacteria, Tenericutes, and Verrucomicrobia in the GH group, suggesting partial restoration of microbiota at the phylum level post-6-Gingerol treatment.

At the species level, the most abundant taxa were Lactobacillus murinus, unclassified_f__Lachnospiraceae, and unclassified_g__Escherichia/Shigella (Figure 7A). Modeling significantly reduced L. murinus abundance, with no substantial change in the GH group compared to the MOD group. unclassified_f__Lachnospiraceae abundance remained unchanged in the MOD group but decreased in the GH group. Unclassified_g__Escherichia/Shigella significantly increased in the MOD group, with the GH group showing trends towards CON group levels. Using random forest algorithms, we identified potential biomarker taxa, with top 10 ranked by importance (Figure 7B). Stamp analysis identified differences among groups (Figure 7C). Notably, Lactobacillus acidophilus, Bacteroides thetaiotaomicron, Parabacteroides goldsteinii, and Bacteroides acidifaciens were elevated in the GH group (Figures 7D–G). These taxa are closely associated with short-chain fatty acids (SCFAs) production (Modasia et al., 2020; Takei et al., 2020; Vemuri et al., 2019; Wang et al., 2021). To determine whether changes in gut microbiota influence SCFAs production, we conducted targeted SCFAs analysis.

Short-chain fatty acids (SCFAs) have a direct inhibitory effect on the growth of C. difficile and alleviate CDAD symptoms by reducing intestinal inflammation, increasing tight junction protein expression, and modulating the host immune response (Ouyang et al., 2022). Using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), we successfully quantified SCFAs in fecal samples from different groups of mice. The SCFAs analyzed, along with their chemical formulas, are presented in Supplementary Figure S4. Total ion chromatograms (TIC) for standards and fecal samples are shown in Supplementary Figures S6A–E, respectively. Standard curves for each SCFAs are depicted in Supplementary Figure S5.

The results (Figure 8) indicated that, except for isovalerate, the levels of all detected SCFAs were significantly reduced in the MOD group compared to the CON group. Following 6-Gingerol treatment, there was a significant increase in acetate (P < 0.001) (Figure 8A), butyrate (P < 0.01) (Figure 8D), and valerate (P < 0.001) (Figure 8E) levels compared to the MOD group. Other SCFAs also showed notable increases. Notably, acetate, butyrate, and valerate, which exhibited significant differences from the MOD group, have been directly linked to CDAD recovery. Thus, we propose that the restorative effects of 6-Gingerol on CDAD are closely associated with its ability to elevate SCFAs levels.