Gut microbiota profiling revealed the regulating effects of salidroside on iron metabolism in diabetic mice

Abstract

Background: Diabetes is a common metabolic disease that is associated with gut microbiota dysbiosis and iron metabolism. Salidroside (SAL) is the main ingredient of the traditional Chinese herb Rhodiola, previous studies have shown that SAL could reshape the gut microbiota and limit iron accumulation. Therefore, it is possible that SAL can act as an alternative therapy for diabetes, and its underlying mechanism is worth exploring.

Methods: SAL was used to treat diabetic db/db mice. Serum glucose and iron levels and the histopathology of myocardial fibres were evaluated. The gut microbiota composition was determined by 16S rRNA Illumina sequencing technology.

Results: Treatment with SAL significantly reduced blood glucose and ameliorated diabetic cardiomyopathy in diabetic db/db mice, which was accompanied by inhibited ferroptosis and iron accumulation. Furthermore, the 16S rRNA sequencing results showed that SAL induced a change in the gut microbiota composition. Overall, SAL could increase the proportion of probiotic bacteria and decrease Lactobacillus to improve gut microbiota. Specifically, SAL increased the ratio of Bacteroidetes to Firmicutes in diabetic mice. The most significant biomarker was the genus Lactobacillus between the MD group and the SAL group. In addition, COG and KEGG analyses suggested that SAL mainly participated in nutrient metabolism, among them iron metabolism was associated with the abundance of Lactobacillus.

Conclusions: SAL could reduce the glucose level and protect against diabetic cardiomyopathy in diabetic mice, which might be mediated by the change in the gut microbiota and the regulation of iron metabolism. The findings suggested that SAL was a promising complementary option for diabetes therapy.

Keywords: diabetes; gut microbiota; iron metabolism; lactobacillus; salidroside.

Figure 1

Influence of SAL on glucose regulation and diabetic cardiomyopathy in diabetic mice. (A), Changes in the blood glucose and weight of db/db mice during the period of SAL treatment. (**p < 0.05 as MD group vs SAL group). (B), H&E staining of myocardial tissue sections. (C), Transmission electron microscopy of myocardial cells.Green arrow: extravasation of the heart cavity; black arrow: irregularly shaped cavities; red arrow: necrotic cardiomyocytes.

Figure 2

Influence of SAL on the expression of myocardial injury markers in diabetic mice. (A), Immunohistochemistry of cTNT and GPX4 in myocardial tissue. (B), The optical density value (IOD) of the brown colour of cTNT staining in myocardial tissue. (C), The IOD value of the brown colour of GPX4 staining in myocardial tissue. (ns, no statistical significance; *p < 0.05 as MD group vs WT group; **p < 0.05 as MD group vs SAL group).

Figure 3

Influence of SAL on iron metabolism in diabetic mice. (A), The serum iron levels of mice in the different groups; (B), The transferrin levels of mice in the different groups; (C) Western blot analysis of the protein expression of SLC7A11, LC3II, and GAPDH in myocardial tissue; (D) Grey value analysis of the western blot results. (ns, no statistical significance; *p < 0.05 as MD group vs WT group; **p < 0.05 as MD group vs SAL group). ***means that SAL group compared with WT group is difference significant.

Figure 4

Changes in the gut microbiota of mice in the different groups. (A), The overall composition of the gut microbiota at the phylum level. (B), Sankey plot of the changes in the composition of the gut microbiota at the genus level.

Figure 5

Assessment of significantly different species between groups. (A), Random forest analysis was combined with a difference test indicating significant differences in different groups and the importance of classification between groups. The * on the right represents the significance of the difference between groups (Kruskal–Wallis rank-sum test) (\***p < 0.001; \**p < 0.01; \*p < 0.05). (B), LDA scores plot. The horizontal coordinates were the logarithmic scores of LDA for each classification unit. The vertical coordinates were the classification units with significant difference between groups. The longer the length, the more significant the difference was.

Figure 6

Functional prediction and analysis of SAL-related bacteria. (A), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways by Tax4Fun tools at level 2 and level 3. (B), Correlation analysis between high-abundance genera and iron metabolism and glucose metabolism. Color depth indicates correlation, the more red indicates the stronger negative correlation, the more green indicates the stronger positive correlation, and the asterisk indicates significance (\**p < 0.01; \*p < 0.05).