Dapagliflozin-affected endothelial dysfunction and altered gut microbiota in mice with heart failure

Aim: To investigate the potential microbiome profile of a mouse model with heart failure (HF) during dapagliflozin treatment. Method: An HF model was constructed in 8-week-old male mice, and cardiac tissues were analyzed using histological staining. Hemodynamic indexes were measured, and fecal samples were collected for 16S rDNA sequencing. Chao1, Shannon, and Simpson were used for a-diversity analysis. b-Diversity analysis was conducted using principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS) based on the Bray–Curtis distance. Linear discriminant analysis coupled with effect size measurements (LEfSe) was used to identify signature gut microbiota, and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) was used to predict the function of altered gut microbiota. Result: Dapagliflozin treatment reduced inflammation, infarction area, and cardiac fibrosis in HF mice. It also increased endothelial-dependent dilation and inflammation in mice with HF. Dapagliflozin decreased the ratio of Firmicutes/ Bacteroidetes, which was increased in HF mice. There was no significant statistical difference in a-diversity among the control, HF, and HF+dapagliflozin groups. Desulfovibrio, AF12, and Paraprevotella were enriched in HF+dapagliflozin, while Rikenella and Mucispirillum were enriched in HF based on LEfSe. KEGG analysis revealed that altered gut microbiota was associated with fermentation, amino acid biosynthesis, nucleoside and nucleotide biosynthesis/degradation, fatty acid and lipid biosynthesis, carbohydrate biosynthesis/degradation, and cofactor/prosthetic group/ electron carrier/vitamin biosynthesis. Conclusion: Understanding the microbiome profile helps elucidate the mechanism of dapagliflozin for HF. The signature genera identified in this study could be used as a convenient method to distinguish between HF patients and healthy individuals.