Fructooligosaccharides (FOS) (Orafti^® P95; degree of polymerization (DP) 2–8; purity ≈ 95%) and inulin (INU) (Orafti^®HP; DP ≥ 23; purity ≈ 100%) were sourced from Beneo (Tienen, Belgium). Galacto-oligosaccharides (GOS) (DP 2–8; purity ≥ 70%), isomalto-oligosaccharides (IMO) (DP 5–11; purity ≈ 90%), and xylo-oligosaccharides (XOS) (DP 2–7; purity ≈ 95%) were obtained from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China), and oat β-glucan (BG) (the molecular weight at 2,000,000 Da; purity ≈ 75%) was purchased from Jiahe Xuri Food Co., Ltd. (Henan Province, China). Glucose, fructose, xylose, and galactose were supplied by Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Tannic acid (TA) was provided by Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). All other chemicals and reagents utilized were of chromatographic or analytical grade.

Fresh fecal samples were donated by three healthy donors with a body mass index of 18.5–23.9, who had no known metabolic or gastrointestinal diseases and had not taken antibiotics and probiotic products for at least 3 months. Fresh feces were collected using the stool collectors (Sangon Biotech, Shanghai, China) and placed under anaerobic conditions (90% N₂, 5% CO₂, 5% H₂) within 15 min. Fresh feces samples from each donor were mixed and dissolved in sterile phosphate buffer (25%, w/w) by vortex and filtered through four-layer sterile medical gauze to obtain the fecal slurry. In vitro fermentation was conducted according to the protocol previously reported (Olano-Martin et al., 2000). According to our previous study (Liu et al., 2024b), 0.5 μmol/mL TA had no significant effect on the fermentation rate of resistant starch, and 1.5 μmol/mL TA had a stronger ability to decrease the fermentation rate of resistant starch than 1.0 μmol/mL TA. Moreover, 0.5–2.0 μmol/mL TA increased the total bacterial number. Therefore, the TA concentration was set as 1.5 μmol/mL. The concentration of dietary fibers was set up according to the previous report (He X. et al., 2023; He X. X. et al., 2023). The basic medium (1.0 L) was composed of peptone (2.0 g), yeast extract (2.0 g), NaHCO₃ (2.0 g), L-cysteine hydrochloride (0.5 g), bile salts (0.5 g), NaCl (0.1 g), K₂HPO₄ (0.04 g), KH₂PO₄ (0.04 g), MgSO₄·7H₂O (0.01 g), CaCl₂·H₂O (0.01 g), haemin (5.0 mg), vitamin K₁ (10.0 μL), Tween 80 (2.0 mL) and resazurin (1.0 mg). To initiate fermentation, 0.2 mL fecal slurry was added into 4.8 mL medium, which was the control group. The fermentation media with 1.5 μmol/mL TA or 10 mg/mL INU, FOS, XOS, GOS, IMO, and BG were used as positive control groups, which were named the TA group, the INU group, the FOS group, the XOS group, the GOS group, the IMO group, and the BG group, respectively. The fermentation media with mixtures of 1.5 μmol/mL TA and 10 mg/mL INU, FOS, XOS, GOS, IMO, or BG were named the TA_INU group, the TA_FOS group, the TA_XOS group, the TA_GOS group, the TA_IMO group, and the TA_BG group, respectively. Fermentation was carried out in a vibrating incubator (37 °C, 120 rpm). The fermentation samples were collected at 0, 3, 6, 12, 24, and 48 h and stored at −80 °C for further analysis.

On the other hand, glucose, fructose, xylose, and galactose were added into the basic media and used as positive control groups, which were named the Glu group, the Fru group, the Xyl group, and the Gal group, respectively. The fermentation media with mixtures of 1.5 μmol/mL TA and 10 mg/mL glucose, fructose, xylose, or galactose were named the TA_Glu group, the TA_Fru group, the TA_Xyl group, or the TA_Gal group, respectively.

Gas was collected by syringes and its production was measured. Besides, the pH of the fermentation broth was measured using a standard pH meter (Mettler Toledo, China).

The concentration of acetate, propionate, and butyrate during fermentation was quantified by a gas chromatography system (7890B, Agilent Technologies, United States) equipped with an HP-FFAP capillary column (19091F-43, 30 m × 250 μm × 0.25 μm, Agilent Technologies, United States) and a flame ionization detector. The fermentation samples were centrifuged at 12,500 g for 5 min to obtain the supernatant. The supernatant was filtered using a 0.22-μm syringe filter, and 1 M HCl solution and 1 mM 2-ethylbutyric acid solution (the internal standard) were added. Subsequently, 1 μL treated sample was injected into the gas chromatography system. Helium was used as the carrier gas at a flow rate of 30 mL/min. The temperature was held at 60 °C for 5 min, then increased to 160 °C at a rate of 10 °C/min and held for 2 min, and increased to 220 °C at a rate of 20 °C/min. The injector and detector temperatures were maintained at 220 °C and 260 °C, respectively. Calibration curves were constructed using acetate, propionate, and butyrate standards, and concentrations were calculated based on response factors relative to 2-ethylbutyric acid.

The fermentation broth supernatant was filtered using a 0.22-μm syringe filter, and the gallic acid concentration was detected using a liquid chromatography system with a UV detector (1,260, Agilent Technologies, United States). UV detection was performed at 280 nm. A Poroshell 120 SB-C18 column (4.6 × 150 mm, 4 μm; Agilent Technologies, United States) was used. The column temperature was maintained at 30 °C, and the injection volume was 5 μL. The mobile phase consisted of 0.1% phosphoric acid solution (Eluent A) and acetonitrile (Eluent B) at a flow rate of 0.8 mL/min. The gradient was established by mixing Eluent A (0–11 min, 80–50%; 11–17 min, 50–80%) and Eluent B (0–11 min, 20–50%; 11–17 min, 50–20%).

Tannic acid (1.5 μmol/mL) was added into the control fermentation broth, and the activity of glycoside hydrolases before and after the addition of tannic acid was determined. The β-glucanase, xylanase, α-glucosidase, and β-galactosidase activity of the control group was determined using the β-glucanase activity assay kit (K-MBGL; Megazyme International Ireland, Bray, Ireland), xylanase activity assay kit (T-XAX; Megazyme International Ireland, Bray, Ireland), α-gucosidase activity assay kit (Beijing Solarbio Science & Technology Co., Ltd.) and β-galactosidase activity assay kit (Beijing Solarbio Science & Technology Co., Ltd.) according to the manufacturers’ protocols.

Due to lack of commercially available assay kits, the β-fructosidase activity was assessed by monitoring the fructose concentration during fermentation (Paludan-Müller et al., 2002). The fructose concentration was determined using a Dionex ICS-6000 ion chromatography system (Thermo Fisher Scientific, Waltham, MA, United States). The system consisted of a dual-piston pump, an AS-SP autosampler, and a DC electrochemical detector. The electrochemical detector employed an Ag/AgCl reference electrode and a gold working electrode, applying the standard carbohydrate quadrupole waveform. A CarboPac™ PA20 guard column (3.0 mm × 30 mm, Thermo Fischer Scientific, Waltham, MA, United States) and a CarboPac™ PA20 analytical column (3.0 × 150 mm, Thermo Fischer Scientific, Waltham, MA, United States) were used. The supernatant was filtered through a 0.22-μm syringe filter, and 25 μL sample was injected. The mobile phase was composed of ultrapure water (Eluent A), 10 mmol/L NaOH solution (Eluent B), 250 mmol/L NaOH solution (Eluent C), and 500 mmol/L CH₃COONa solution (Eluent D). The gradient was established by mixing Eluent B (0–20 min, 10%; 20–30 min, 20%; 48–60 min, 10%), Eluent C (30–48 min, 80%) and Eluent D (20–30 min, 10–40%), supplemented by Eluent A to 100%. The temperature was set as 30 °C, and the flow rate was 0.5 mL/min. Chromeleon 7 software was utilized for data processing. The fructose concentration in fermentation broth was quantified using a calibration curve by comparing the peak area to that of standard solutions.

DNA was extracted from the fecal fermentation slurry, and its quantity and quality were evaluated using UV spectrophotometry and agarose gel electrophoresis. Absorbance at 260 nm and 280 nm was measured to calculate the DNA concentration. Generally, an A260/A280 ratio of 1.8–2.0 indicates high purity. Additionally, DNA was separated via agarose gel electrophoresis, and bands were visualized using a gel imaging system. Clear and intact bands confirmed DNA suitability for subsequent experimental applications. The V3-V4 region of the 16S rRNA gene was amplified from each sample using polymerase chain reaction (PCR). The amplification was performed with the forward primer 338F (5’-ACTCCTACGGGAGGCAGCA-3′) and the reverse primer 806R (5’-GGACTACCAGGGTATCTAAT-3′). The amplicons were quantified using the PicoGreen dsDNA Assay Kit to ensure accurate measurement of the DNA concentration. Following individual quantification, equimolar amounts of amplicons were pooled to create a normalized library for sequencing. After the individual quantification step, amplicons were pooled in equal amounts, and pair-end 2,250 bp sequencing was performed using the Illlumina NovaSeq platform with NovaSeq 6,000 SP Reagent Kit (500 cycles) at Shanghai Personal Biotechnology Co., Ltd. (Shanghai, China). Microbiome bioinformatics were performed with QIIME2 2022.11. Briefly, raw sequence data were demultiplexed using the demux plugin following by primers cutting with cutadapt plugin. Sequences were then quality filtered, denoised, merged and chimera removed using the DADA2 plugin. Non-singleton amplicon sequence variants (ASVs) were aligned with mafft and used to construct a phylogeny with fasttree2. Alpha-diversity metrics, including Chao1, observed species, Shannon, Simpson, Faith’s PD, Pielou’s evenness and Good’s coverage, and beta diversity metrics, including weighted UniFrac, unweighted UniFrac, Jaccard distance, and Bray–Curtis dissimilarity, were estimated using the diversity plugin with samples were rarefied to 35,891 sequences per sample. Taxonomy was assigned to ASVs using the classify-sklearn naïve Bayes taxonomy classifier in feature-classifier plugin against the Greengenes 13.8 Database. The resulting sequencing data were analyzed to characterize the microbial composition and to assess both α-diversity (within-sample diversity) and β-diversity (between-sample diversity) based on operational taxonomic units (OTUs).

All tests in this study were performed at least in triplicate, and data are expressed as the mean ± standard deviation. Statistical analyses and graphical displays were performed using SPSS Statistics 26.0 (SPSS, Inc., Chicago, Illinois) and GraphPad Prism 9.0 (GraphPad Software, Inc., La Jolla, California). Data in Figures 1–3 were analyzed by two-way analysis of variance (ANOVA), and data in Figures 4, 5 were analyzed by one-way ANOVA. Statistical significance was established at p < 0.05. Statistical analysis of microbiota was performed using R¹.

There was no significant difference in gas production, pH, and production of SCFAs between the TA group and the control group (Figures 1, 2). Groups containing dietary fibers exhibited significantly higher gas and SCFA production and lower pH values than the control group. Moreover, the gas and SCFA production of groups containing INU, FOS, XOS, GOS, IMO, or BG increased rapidly from 0 to 6 h and the pH decreased rapidly, suggesting that these dietary fibers were metabolized rapidly. Notably, the TA/dietary fiber mixture groups had lower gas and SCFA production and higher pH than groups supplemented with only FOS, INU, XOS, GOS, IMO, or BG, which demonstrate that the addition of 1.5 μmol/mL TA effectively reduced the fermentation rate of these dietary fibers.

Moreover, the supplementation of TA exerted differential effects on the production of individual acetate, propionate, and butyrate from fermentation of different dietary fibers. Specifically, the addition of TA decreased the acetate, propionate and butyrate production from fermentation of INU, FOS, XOS and BG throughout the entire fermentation. TA led to a decrease in the production of acetate and propionate from fermentation of GOS. However, the butyrate production showed a significant increase at the late stage of fermentation (24–48 h). Accordingly, the TA_GOS group had more butyrate than the GOS group. This result might be due to that TA promoted the growth of butyrate-producing bacteria during fermentation of GOS. Analogously, the TA_IMO group had less acetate and more butyrate and propionate than the IMO group at the late stage of fermentation. The effect of TA on fermentation of resistant starch was different from those described above (Liu et al., 2024b). Similarly, rutin altered patterns of SCFA production from fermentation of pectin, psyllium, and resistant maltodextrin (Havlik et al., 2020). However, purple sweet potato polyphenols had no impact on SCFA production from fermentation of INU (Kilua et al., 2019). These differences might be associated with the different effects of polyphenol/dietary fiber on the composition of gut microbiota and the different polyphenol concentrations.

As stated above, we previously confirmed that TA reduced the fermentation rate of resistant starch, because TA inhibited the amylase activity of gut bacteria. It has been reported that polyphenols can also inhibit the activity of various enzymes except amylases, such as protease, glucosidase, phospholipases A2, and lipase (El-Saadony et al., 2024; He X. et al., 2023; Kan et al., 2022). The inhibitory effect of polyphenols on the activity of enzymes mainly results from the binding interaction between polyphenol molecules and enzyme molecules (Miao, et al., 2021; Yu et al., 2024). It is possible that this interaction widely exists between polyphenol molecules and protein molecules. Thus, it is inferred that TA was able to inhibit glycoside hydrolases that hydrolyzed fibers used in this work and thus decrease the fermentation rate of these fibers. On the other hand, monosaccharides resulting from hydrolysis of dietary fibers are further metabolized to produce SCFAs, which also involves enzymes, such as hexokinase, phosphofructokinase and pyruvate kinase. In other words, TA might also inhibit the activity of these enzymes and decrease the fermentation rate of dietary fibers. Accordingly, the effect of TA on the activity of β-fructosidase, xylanase, β-galactosidase, α-glucosidase, and β-glucanase was determined, and the effect of TA on fermentation of monosaccharides, including glucose, fructose, xylose, and galactose, was studied.

β-fructosidase hydrolyzes INU or FOS to release fructose. Thus, the β-fructosidase activity was assessed by the fructose concentration. During fermentation, the fructose concentration in the INU group gradually increased (Figure 3A), indicating that INU was gradually hydrolyzed by β-fructosidase secreted by gut microbiota to release free fructose. The fructose concentration in the FOS group reached the peak value after fermentation for 3 h and then slightly decreased (Figure 3B), which suggests that FOS was rapidly hydrolyzed into fructose and metabolized to SCFAs by gut bacteria. This metabolic difference of FOS and INU might be due to lower degree of polymerization of FOS than INU. It is noteworthy that at the early stage of fermentation (0–6 h), the TA_INU group or the TA_FOS group had lower fructose concentration than the group containing INU or FOS alone. The fructose concentration in the TA_INU group or the TA_FOS group increased progressively during fermentation and was similar to that of the INU group or the FOS group after fermentation for 48 h. These results demonstrate that TA effectively inhibited the β-fructosidase activity. Similarly, the addition of TA significantly decreased the activity of xylanase, β-galactosidase, α-glucosidase, and β-glucanase (Figures 3C–F). These results confirm that TA inhibited the activity of enzymes that participated in the first fermentation stage of dietary fibers.

The gas production in monosaccharide groups increased rapidly during the first 6 h (Figure 4A), indicating that these monosaccharides were rapidly metabolized. In the TA/monosaccharide mixture groups, the gas production was significantly reduced. Concurrently, the addition of TA decreased acid production from fermentation of monosaccharides. During fermentation, the pH of the TA/monosaccharide mixture groups was higher than that of groups with only monosaccharides (Figure 4B). Regarding SCFA generation, the groups containing monosaccharides demonstrated rapid accumulation of total SCFAs during the first 6 h, and the addition of TA substantially inhibited production of total SCFAs. Specifically, production of acetate, propionate, butyrate, and total SCFAs in TA/monosaccharide mixture groups was lower than that of groups with only monosaccharides (Figures 3C–F). These results indicate that TA slowed down fermentation of monosaccharides. Thus, it is inferred that TA also inhibited the activity of enzymes that participated in the second fermentation stage of dietary fibers. As a result, TA slowed down fermentation of dietary fibers. In summary, TA slowed down the whole metabolic process of dietary fibers due to its inhibitory effect on universal enzymes.

The TA is hydrolyzed into gallic acid, and gallic acid is further metabolized into urolithin by gut microbiota (Loo et al., 2020; Nakamura et al., 2003). Consequently, the gallic acid concentration was examined to assess effects of dietary fibers on the metabolic pattern of TA. The gallic acid concentration in the TA group reached the peak value at 3 h and then decreased (Figure 5), indicating that TA was rapidly hydrolyzed by gut microbiota. The gallic acid concentration in TA_INU, TA_XOS, TA_GOS, and TA_BG groups also reached the peak value at 3 h. Besides, the gallic acid concentration at 3 h was higher in the TA_XOS group and the TA_BG group than in the TA group, indicating that XOS and BG promoted the hydrolysis degree of TA. In contrast, the TA_INU group and the TA_GOS group exhibited lower gallic acid concentration than the TA group, suggesting that INU and GOS reduced the hydrolysis degree of TA. Particularly, the gallic acid concentration reached the peak value at 48 h in the TA_FOS group and the TA_IMO group, which suggests that FOS and IMO significantly slowed down the metabolism of TA. Thus, it is suggested that dietary fibers affected the metabolism of TA, depending on the dietary fiber type. Yang et al. (2021) found that the addition of FOS slowed down the degradation of cyanidin-3-O-glucoside, and the mixture group had lower abundance of Fusobacterium than the cyanidin-3-O-glucoside group. Moreover, it was reported that RG-I pectic polysaccharides modulated the metabolic of hesperidin by promoting the growth of Blautia, Faecalibacterium, and Prevotella (Wu et al., 2025). Therefore, it was inferred that XOS and BG promoted growth of TA-metabolizing bacteria and the degradation of TA. Moreover, other four dietary fibers inhibited the growth of TA-metabolizing bacteria, thus inhibiting or slowing down the degradation of TA.