The altered gut microbiota of high-purine-induced hyperuricemia rats and its correlation with hyperuricemia

Animals

Animals for this study were obtained from Qingdao qinda biotechnology Co.,Ltd. All experimental animals were approved by the Animal Research Ethics Committee of the Affiliated Hospital of Qingdao University; Approval No. AHQU-MAL2017022). All animals were housed individually in a sterile and ventilated cage at standard temperature (24 ± 1  ^∘C) and humidity (65%–70%) with lights on 12-h light-dark cycle. Before the experiment, the rats were fed normal forage and water. The rats that had been anesthetized with inhaled diethyl ether were sacrificed by decapitation after the experiment.

Hyperuricemia rat modeling and feces and blood sampling

Forty-eight 6-week-old male Wistar rats were assigned to the hyperuricemia group (HUA, n = 29) and the normal group (N, n = 19). The HUA group was fed yeast-rich forage and gavaged with purine at 100 mg/(Kg ⋅ d), whereas the N group was fed normal forage and gavaged with the same volume of water. After 5 weeks, fresh feces were obtained by stimulating the anus. Rats that had been fasted overnight were anesthetized briefly with inhaled diethyl ether, and the blood samples were collected from the intra-orbital retrobulbar plexus. Blood was used for uric acid measurements while feces were stored at −80 °C and used for analysis of gut bacterial community.

Antibiotics interference of gut microbiota and feces and blood collection

32 male Wistar rats (6 weeks old) were randomly divided into four groups, with 8 rats in each group. The normal group (N) was fed water, whereas the hyperuricemia group (HUA) was administrated yeast-rich forage and gavaged with purine at 100 mg/(Kg ⋅ d). Antibiotics were used as before (Hu et al., 2015), with minor modifications. Antibiotics-fed hyperuricemia group (Ab+HUA) was administrated yeast-rich forage, gavaged with purine at 100 mg/(Kg ⋅ d) and supplemented with water with antibiotic mixture (ampicillin 250 mg/kg + neomycin 250 mg/kg + metronidazole 50 mg/kg). Antibiotics-fed normal group (Ab+N) was gavaged with water supplemented with antibiotic mixture (ampicillin 250 mg/kg + neomycin 250 mg/kg + metronidazole 50 mg/kg). The experiment lasted five weeks during which purine and antibiotic mixture were administered once daily. Throughout the experiment, orbital blood and fresh feces were collected once a week and used to measure the biochemical indicators and analyze the intestinal microbiota, respectively.

Recipient rat modeling and fecal microbiota transplantation

Germ-free intestinal environment of recipient rats was stimulated following reported methods with minor modifications (Zhao et al., 2018). Twenty normal rats were given water supplemented with antibiotic mixture (ampicillin 250 mg/kg + neomycin 250 mg/kg + metronidazole 50 mg/kg) daily by gavage. Twelve days later, the fecal microbiota of rats was analyzed to ensure that the intestinal environment was as sterile as possible. Then twenty recipient rats were randomly assigned to a normal microbiota transplantation group (NMT) and a hyperuricemia microbiota transplantation group (HMT), with each group containing 10 rats. Fresh feces from the HUA and normal rats in the previous experiment were collected separately. As reported previously, the fresh feces were immediately homogenized in pre-reduced PBS at 1 ml per pellet (Yano et al., 2015). Fecal solution (one mL) was gavaged to all the recipient rats for one consecutive week. NMT group was gavaged with fecal solution of N rats, whereas HMT group was gavaged with the fecal solution of HUA rats. Fresh feces and orbital blood were collected every other week after continuous transplantation for one week. All rats were fed normal forage and water throughout the experiment.

454 pyrosequencing

DNA from the frozen feces was extracted using the E.Z.N.A.^® Stool DNA Kit (OMEGA, America). The quality of DNA was analyzed using a NanoDrop-2000 spectrophotometer (Thermo Scientific). The V1-V3 variable regions of the 16S rRNA genes were amplified using the primers 27F (5′-AGA GTT TGA TCC TGG CTC AG -3′) and 533R (5′-TTA CCG CGG CTG CTG GCA C-3′) in a 20 µL mixture containing 4 µL of Phusion HF buffer, 0.8 µL of forward primer (5 µM), 0.8 µL of reverse primer (5 µM), 0.4 µL of dNTP (10 mmol/L each), 0.2 µL of Phusion DNA polymerase, and 10ng of fecal DNA as template. The reaction was performed with following PCR program: denaturation at 98 °C for 30 s, followed by 25 cycles of denaturation at 98 °C for 10 s; annealing at 55 °C for 30 s and extension at 72 °C for 30 s; and a final extension at 72 °C for 5 min. Agarose gel (2%) electrophoresis was used to purify the PCR product, and the purified product was sequenced on Roche GS-FLX platform.

High-throughput sequencing on Illumina MiSeq platform

DNA was extracted with the E.Z.N.A.^® Stool DNA Kit. 16S rRNA genes (V3-V4 variable regions) were amplified with the primers 338F (5′-ACT CCT ACG GGA GGC AGC AG -3′) and 806R (5′-GGA CTA CHV GGG TWT CTA AT -3′). The amplification reaction was performed in a 25 µL volume containing 12.5 µL of Pusion Hot start flex 2X Master Mix, 2.5 µL of forward primer, 2.5 µL of reverse primer, and 50 ng of template DNA. The reaction was performed with following PCR program: denaturation at 98 °C for 30 s, followed by 35 cycles of denaturation at 98 °C for 10 s, annealing at 54 °C for 30 s and extension at 72 °C for 45 s, and a final extension at 72 °C for 10 min. The PCR product was purified through agarose gel (2%) electrophoresis and commercial sequencing was conducted on Illumina MiSeq platform.

Sequence analysis

The raw sequencing reads were processed by splicing and filtering with the clean data clustered into operational taxonomic units (OTUs) by ≥97% sequence similarity. The gut microbial diversity was determined by the abundances of OTUs in different samples. Species annotation was performed by comparing the representative sequence of each OTU with the 16S rDNA database. LEfSe analysis identified the discrepant microbial species between groups. The Spearman’s rank correlation analysis was used to find the relationship between the gut microbiota and hyperuricemia.

Statistical analysis

All data are presented as the mean ± standard deviation (SD). All biochemical data and microbial data from the two groups were compared using Student’s unpaired t-test and Wilcoxon rank-sum test, respectively. Similarly, biochemical data and microbial data from multiple groups were compared using one-way ANOVA and Kruskal-Wallis test, respectively. P-values <0.05 were considered statistically significance. The data was analyzed using SPSS and R software.

The uric acid content of HUA rats increased significantly

In the fifth week of establishing the HUA model, the uric acid (UA), blood urea nitrogen (BUN), creatinine (Cr) and total cholesterol (TC) were found to be significantly different between the two groups (Table S1). The elevated UA levels in HUA rats indicated that the hyperuricemia model was successfully established (Fig. 1A). BUN and Cr levels in HUA rats were significantly elevated compared to that in N rats, indicating that the renal function indices in HUA rats were abnormal. TC was also significantly elevated in HUA rats, indicating that the lipid metabolism of HUA rats was abnormal.

The change of gut microbiota in HUA rats

In order to assess the consequence of grouping in the HUA model, we compared the microbial differences among and within groups and displayed as a boxplot based on Anosim analysis. We found that intra-group differences were smaller than inter-group differences (Fig. 1B). The higher Shannon index of the HUA group verified an altered microbial diversity in HUA rats (Fig. 2A). PCoA analysis implied a significant microbiota differences between HUA and N rats (Fig. 2B). The relative abundance of Bacteroidetes in the HUA rats was lower than that of N rats, and the relative abundance of Firmicutes and Actinobacteria in the HUA rats was higher than that of N rats (Figs. 2C and 2D). These results suggested that the gut microbiota of the HUA rats had changed in comparison with that of N rats.

LEfSe analysis identified the discrepant microbial taxa (LDA score >2) between HUA and N rats. Genera Prevotella, Anaerovibrio, Alloprevotella, Barnesiella among others were less abundant in the gut of HUA rats than that of N rats. Conversely, genera Allobaculum, Clostridium_XlVa, Flavonifractor, Phascolarctobacterium, Clostridium_XVIII, Parabacteroides, Robinsoniella, Subdoligranulum, Catabacter, Blautia, Bacteroides, Olsenella among others were more abundant in the intestinal tract of HUA rats than that of N rats (Fig. 3). Bacteria including Olsenella, Clostridiales_unclassified, Peptococcaceae_unclassified, Blautia and Lachnospiracea_incertae_sedis were significantly and positively correlated with UA. Only Prevotellaceae_unclassified and Prevotella were significantly and negatively correlated with UA (Table S2). These altered microbial taxa and the correlation between gut bacteria and UA suggest that the gut microbiota may have some roles in hyperuricemia.

Decreased uric acid content in Ab-fed HUA rats

To explore the potential roles played by gut microbiota, we interfered with the gut microbiota of the rats with antibiotics and compared the degree of UA elevation between the HUA rats and the Ab-fed HUA rats. As shown in Fig. 4A, compared with the N rats, UA levels in HUA rats increased significantly from the second week to the fifth week, indicating that the established hyperuricemia model was successfully maintained. We then compared the gut microbiome of the HUA and the N rats and found that the gut microbiome of the HUA rats had changed (Fig. S1). The reproducibility of the result suggested that gut microbiota and hyperuricemia are associated with each other.

The UA level in the HUA rats was found to be significantly elevated than that in N rats. Similarly, the Cr, BUN, high density lipoprotein (HDL) and low-density lipoprotein (LDL) in HUA rats were also significantly elevated than those in N rats. These findings indicated that the renal function indices and lipid metabolism in HUA rats are abnormal (Fig. 4B through Fig. 4E). In contrast, UA level in Ab-fed HUA rats was significantly lower than that in HUA rats; however UA level was still significantly higher in the Ab-fed HUA rats than in N rats (Fig. 4A), and Cr, BUN and LDL was similar between the Ab-fed HUA and the HUA rats (Figs. 4B, 4C and 4E). Furthermore, HDL in the Ab-fed HUA rats was also significantly lower than that in the HUA rats from the third week to the fifth week of the experiment (Fig. 4D).

The disturbed gut microbiota in Ab-fed HUA rats

We analyzed fecal microbiota from the third week of the experiment. As expected, antibiotics significantly reduced the richness of gut microbiota of the Ab-fed HUA rats (Fig. 4F), which resulted in the difference between the Ab-fed HUA and the HUA rat gut microbiome (Fig. 4G). In combination with the lower uric acid content, the altered gut microbiota of the Ab-fed HUA rats suggested that gut microbiota may have a potential role in hyperuricemia.

Fecal microbiota from HUA rats increased uric acid content of recipient rats

After antibiotics intervention, the relative abundance of the dominant phyla (Bacteroidetes, Firmicutes, Proteobacteria, Bacteria_unclassified, etc.) and microbial composition of rats in the first week altered significantly (Fig. S2). The dramatic decrease in richness (Fig. 5A) and diversity (Fig. 5B and Fig. S2) of the gut microbiota (P < 0.001) in the first week revealed that the recipient rat model was successfully established. After the transplantation, the relative abundance of the dominant phyla (Bacteroidetes, Firmicutes, Proteobacteria, Bacteria_unclassified, etc.) and the microbial composition of the recipient rats also altered significantly (Fig. S2). The richness and diversity of gut microbiota of recipient rats increased to the original (P > 0.05) (Figs. 5A and 5B). Besides, a similar dominant phylum existed in the donor (HUA and N) and the recipient rats (HMT and NMT) (Figs. 5C and 5D). The abundance of dominant phyla Firmicutes, Bacteroidetes, Proteobacteria and Bacteria_unclassified in the recipient rats did not differ from that in the donors (P > 0.05) (Figs. 5E and 5F), implying that the fecal microbiota from the donors has altered the gut microbiota of the recipient rats, and that the gut microbiome of recipient rats is closer to donors.

The uric acid content of the recipient rats in the HMT group increased significantly in comparison to that in the NMT group at the third week after transplantation (week 5). Cr, BUN, HDL and LDL were not significantly different between the HMT group and the NMT group. Increased uric acid content in the recipient rats indicated that the fecal microbiota from the HUA rats may have been involved in hyperuricemia (Fig. 6).

The microbial taxa may associate with the occurrence of hyperuricemia

We found that the genera Vallitalea, Christensenella and Insolitispirillum were all enriched in the HUA and the HMT groups (Tables S3 and S4). Such similarity implies that these microbial taxa may associate with the occurrence of hyperuricemia. However, the specific biological function and pathogenesis of these microbial taxa in the occurrence of hyperuricemia needs further study.