KGM (KGM-M) with 90% purity was provided by Huaxianzi Konjac Products Co., Ltd. (Hubei, China). All other chemicals and reagents used were at least of analytical grade.

The fermentation of KGM in vitro was carried out according to the previous study (16). In brief, 4.5 g of yeast extract, 3.0 g of tryptone, 3.0 g of peptone, 0.5 g of mucin, 0.4 g of bile salt, 0.8 g of L-cysteine hydrochloride monohydrate, 4.5 g of NaCl, 2.5 g of KCl, 0.45 g of MgCl₂·6H₂O, 0.2 g of CaCl₂·6H₂O, 0.4 g of KH₂PO₄, 0.05 g of hemoglobin, and 1 mL of Tween 80 were dissolved in 1 L of distilled water to provide a basal nutrient medium after pH adjusting (to 7.0) and then autoclaved at 121°C for 20 min. Fecal samples were donated by three healthy volunteers (males, 20–30 years old) and three patients with HUA (males, 20–30 years old). The study was approved by the institutional review board of Panyu Central Hospital (IRB approval number: PYRC-2022-015), and written informed consent was obtained from all participants. Following collection, an equivalent mass of fecal samples obtained from healthy volunteers were mixed with sterilized physiological saline solution and centrifuged at 500 g for 5 min to obtain 10% healthy fecal suspension, which was regarded as the NOR group. Similarly, 10% HUA fecal suspension was obtained and named as the HUA group. Then, 1 mL of fecal supernatant was inoculated into a growth basal medium containing glucose or KGM (10 g/L), and healthy fecal samples were designated as the NOR-GLU and NOR-KGM groups, while HUA fecal samples were designated as the HUA-GLU and HUA-KGM groups. All samples were cultured in an anaerobic bag system at 37°C. After fermentation for 24 h, the samples were collected for further experiments.

The inhibitory effect of fermentation samples on XOD activity was determined according to the following steps. Initially, 450 μL of 10 U/L XOD solution, 750 μL of fecal fermentation sample solution, and 525 μL of phosphate-buffered saline (PBS) solution were mixed uniformly. After incubating at 25°C for 15 min, 900 μL of 150 μmol/L of xanthine solution was added, followed by another incubation at 25°C for 30 min. The reaction was terminated by adding 375 μL of 1 mol/L of hydrochloric acid solution, and the absorbance was measured at 290 nm. For the positive control, the sample solution was replaced with different concentrations of allopurinol solution. For the sample control, the XOD solution was replaced with PBS. For the blank, the sample solution was replaced with an equal volume of PBS, and both the sample solution and XOD solution were replaced with PBS as the blank control. The inhibition rates of fermentation samples on XOD activity were calculated using the following formula (Equation 1).

SCFAs were measured according to previous research (14). After fermentation, 2 mL of the fermentation samples was taken and centrifuged at 4°C and 10,000 r/min for 5 min. A measure of 1 mL of the supernatant was collected, and then 0.1 mL of 50% H₂SO₄ and 1 mL of ether were added. The mixture was vortexed for 30 s to homogenize and then centrifuged again at 4°C and 10,000 r/min for 5 min. After being placed in a refrigerator at 4°C for 30 min, the upper layer was passed through a 0.45 μm filter membrane and collected in a brown sample vial for further analysis. The determination was carried out using a gas chromatograph equipped with a FID detector. The instrument conditions were as follows: FFAP flexible quartz capillary column measuring 30 m × 0.25 mm × 0.25 μm. The temperature program of the column was set at 100°C and then increased to 150°C at a rate of 5°C/min. Carrier gas was high-purity nitrogen with a purity of ≥99.999%. The carrier gas flow rate was 2 mL/min. The injector temperature was 250°C. The detector temperature (FID) was 280°C. The injection volume was 1 μL. Each sample was measured three times.

The effects of KGM on the structure and composition of gut microbiota were evaluated using beta-diversity analyses (Figure 1). To display the differences of the genus in different samples, principal component analysis (PCA) was used to summarize factors mainly responsible for this difference. It was obvious that the different groups showed significantly different structures and compositions of gut microbiota. The treatment of KGM could shift the structure of HUA intestinal microbiota toward that of the NOR-KGM group as a result of PCA (Figure 1A), suggesting that KGM could improve the balance of HUA gut microbiota. Additionally, PCoA on genus level explained 65.58% of the total variance, indicating that HUA gut microbiota (HUA, HUA-GLU, and HUA-KGM) had different structures compared to those of healthy gut microbiota groups (NOR, NOR-GLU, and NOR-KGM). Furthermore, to determine the communities or species that explain the differences among the groups, LEfSe analysis was used to identify the biological characteristics representing the relationship among the groups. The circle radiating from inside to outside represents the classification level from the phylum level to the genus level. The diameter of the small circle represents the relative abundance of the classification at that level. As shown in Figure 1C, the representative taxa with significant differences among the groups were Parabacteroides, Butyricicoccus, Clostridium, and Phascolarctobacterium in the NOR group; Bacteroides and Megasphaera in the NOR-GLU group; Anaerostipes, Ruminococcus, Lachnospiraceae, and Lachnoclostridium in the NOR-KGM group; Bifidobacterium, Enterobacter, Fusicatenibacter, and Coprococcus in the HUA group; Romboutsia, Intestinibacter, Ruminococcus, Lachnospira, and Turicibacter in the HUA-GLU group; and Megamonas in the HUA-KGM group.

In Figure 2, the compositions of gut microbiota in both NOR and HUA groups were analyzed. In the NOR and its fermentation groups, Megasphaera, Faecalibacterium, Lachnoclostridium, Anaerostipes, Butyricicoccus, Eisenbergiella, and Enterococcus exhibited higher relative abundances than those in the HUA and its fermentation groups. Within the NOR groups, NOR-KGM increased the relative abundances of Megasphaera, Faecalibacterium, Lachnoclostridium, Lachnospiraceae, Anaerostipes, and Ruminococcus, while decreasing the relative abundances of Butyricicoccus, Eisenbergiella, and Enterococcus compared to the NOR group. Consistently, within the HUA groups, HUA-KGM can also increase the relative abundances of Megasphaera, Faecalibacterium, Lachnoclostridium, Lachnospiraceae, Anaerostipes, and Ruminococcus, while the relative abundances of Butyricicoccus, Eisenbergiella, and Enterococcus decreased compared to the HUA group. The glucose was regarded as a carbon source, which could partly improve the HUA gut microbiota by increasing the relative abundance of Megasphaera, Faecalibacterium, Lachnoclostridium, Anaerostipes, and Ruminococcus. However, the effect is much weaker when compared to the HUA group.

The metabolites of intestinal microbiota are the key factors in the protective effects of dietary fiber in the host. SCFAs, including acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid, are the main metabolites of KGM fermentation. In this study, SCFAs were measured to further investigate the fermentation characteristic of KGM and evaluate the potential health-promoting functions. As shown in Figure 3, acetic acid, propionic acid, butyric acid, valeric acid, isobutyric acid, and isovaleric acid were the main metabolites of KGM fermentation. NOR-KGM exhibited a similar increasing effect on acetic acid, propionic acid, butyric acid, isobutyric acid, and isovaleric acid levels in the NOR-GLU group when compared to the NOR group. Moreover, the concentration of butyric acid and valeric acid in the HUA-KGM group was significantly higher than that in the HUA group (p < 0.05), whereas acetic acid, isobutyric acid, and isovaleric acid in the HUA-KGM group were remarkably lower than that in the HUA group (p < 0.05). In addition, there was no significant difference in the total SCFAs level between the NOR (22.01 ± 0.61 mM) and NOR-KGM (23.28 ± 0.41 mM) groups. However, the total SCFAs level was significantly higher in the HUA-KGM group (38.02 ± 1.27 mM) than in the HUA (24.79 ± 0.71 mM) group. The total SCFAs level in the HUA-GLU group was remarkably lower than that in the HUA-KGM group. In particular, KGM could significantly promote the production of acetic acid, butyric acid, valeric acid, isobutyric acid, and isovaleric acid, which was higher than that in the HUA-GLU group. The results indicated that KGM may regulate the concentration of SCFAs, particularly by increasing the content of butyric acid and valeric acid and decreasing acetic acid, isobutyric acid, and isovaleric acid, by improving the composition of intestinal microbiota.

As described above, KGM could significantly increase the production of SCFAs. The inhibition rate of XOD activity of KGM fermentation was further evaluated in vitro. As shown in Figure 4, the XOD activity was decreased in the HUA group compared to the NOR group. In the NOR groups, the inhibitory rate of XOD activity in the NOR-KGM group was increased compared to the NOR group, indicating the potential mechanism of reducing the uric acid activity of KGM by suppressing XOD activity. Consistently, the XOD activity was significantly inhibited in the HUA-KGM group compared to that of the HUA group (p < 0.05). In addition, the inhibition rate of XOD enzyme activity in the HUA-GLU group was significantly lower compared to the HUA-KGM group. It suggested that the metabolites of KGM by intestinal microbiota may be the key factor contributing to the inhibitory effect on XOD activity.

Based on the above results, it has been revealed that the regulation effect of KGM on SCFAs and SCFA-producing microbiota levels was consistent with its effect on XOD activity. Spearman correlation analysis was further used to visualize the relationship among SCFA level, microbiota composition, and inhibition rate of XOD activity. The results are shown in Figure 5, where the blue circle indicates a negative correlation, the red circle displays a positive correlation, and the size of the dots represents the magnitude of the correlation coefficient value. The larger and darker the dots, the stronger the correlation. In this study, the inhibition rate of XOD activity showed a strong negative correlation with the content of propionic acid, while it displayed a strong positive correlation with the concentration of valeric acid. This suggested that the inhibition of XOD activity by gut microbiota may relate to its regulation of SCFAs. Furthermore, there is a strong negative correlation between the relative abundance of Butyricicoccus, Eisenbergiella, and Enterococcus and the inhibition rate of XOD activity, while the relative abundance of Megasphaera, Lachnoclostridium, and Lachnospiraceae has a positive correlation with the inhibition rate of XOD activity, indicating that KGM may promote the production of metabolic product SCFAs by influencing the intestinal microbiota, thereby inhibiting the activity of XOD.