Gut microbiota alters cardiac metabolism and immune system composition in viral myocarditis mice

Figure 1. Schematic diagram of the experimental design.

Figure 2. Myocardial histopathological changes and echocardiography in different groups. (A) Representative H&E and Masson’s trichrome staining images of myocardial tissues from the control, VMC, VMC-FMT, and VMC-ABX groups (n = 5–7/group), original magnification: 4 × and 40×; scale bars = 500 μm and 50 μm. (B) Representative echocardiographic images of the four groups. (C) Bar graphs show the statistical results of the pathological scores and cardiac collagen volume fractions. (D) Statistical analysis of LVEDV, LVESV, LVEF, and LVFS (n = 5–7/group). Data are presented as the means ± SEM. FMT, fecal microbiota transplantation; ABX, antibiotics; CVB3, coxsackievirus B3; H&E, hematoxylin and eosin; LVEDV, left ventricular end-diastolic volume; LVESV, left ventricular end-systolic volume; LVEF, left ventricular ejection fraction; LVFS, left ventricular fractional shortening; SEM, standard error of mean. *p < 0.05, **p < 0.01.

Figure 3. Analysis of gut microbiota structure among different groups. (A,B) Alpha diversity indices, including Shannon and Simpson; (C) Principal coordinate analysis (PCoA) of beta diversity based on Bray–Curtis dissimilarity. (D,E) Mean relative abundance of gut microbiota at the phylum and genus levels. All genera with relative abundance < 0.1% are reported together and labeled as “Others.” (F) Cladogram indicates the phylogenetic distribution of microbiota correlated with the four groups. *p < 0.05, **p < 0.01.

Figure 4. Linear discriminant analysis (LDA) of four groups. LDA identified gut bacterial taxa with significantly different abundances among the groups.

Figure 5. Cardiac metabolism analysis in VMC and VMC-FMT groups. (A) Principal component analysis (PCA) of myocardial metabolites across the control, VMC, VMC-FMT, or VMC-ABX groups. (B) Heatmap shows the relative abundance of myocardial metabolites in the four groups. (C–F) Comparison of metabolomics data between the VMC and VMC-FMT groups: OPLS-DA analysis (C), top FC scores of the important discriminatory metabolites obtained from the OPLS-DA models (D), volcano plot of the differentially accumulated and significantly changed metabolites (E), and differential metabolites enriched in 20 KEGG pathways (F). (G) Heatmap of Spearman’s correlations between the metabolomics of the VIP top 20 and gut microbiota with statistical differences at phylum taxa. The red ellipse indicates a positive correlation, while the blue indicates a negative correlation. The higher the absolute correlation value, the thinner the ellipse. No color indicates that the p > 0.05. Heat maps are drawn using the R software and the corrplot package.

Figure 6. Cardiac metabolism analysis of the VMC and VMC-ABX groups (A–D). Comparison of metabolomics data between the VMC and VMC-ABX groups: OPLS analysis (A); top FC scores of the important discriminatory metabolites (B); volcano plot of the differentially accumulated and significantly changed metabolites (C); and differential metabolites enriched in 20 KEGG pathways (D).

Figure 7. Levels of M1, M2 cells, and their associated cytokines in different groups. (A) Representative gating strategy for macrophages by flow cytometry. (B) Representative flow cytometry images of the frequencies of cardiac M1 cells in four groups (control, VMC, VMC-FMT, and VMC-ABX, n = 5–7/group). (C,D) Frequencies of cardiac M2 cells in different groups. (D, F) Statistical results of the frequencies of M2. (E) The bar graph indicates the statistical results of the frequencies of M1 and M2. (F,G) Levels of cytokines that are associated with M1 and M2: TNF-α, IL-6, IL-1β, IL-10, Arg1, CD206, and CD86. *p < 0.05 and **p < 0.01.

Figure 8. Frequencies of Th1, Th2, Th17, and Treg cells in four groups. (A) Representative gating strategy for Th1, Th2, and Th17 by flow cytometry. (B) Representative flow cytometry images of the frequencies of Th1 cells in different groups. (C) Representative flow cytometry images of the frequencies of Th2 cells in different groups. (D) Representative flow cytometry images of the frequencies of Th17 cells in different groups. (E) Representative gating strategy for Treg by flow cytometry. (F) Representative flow cytometry images of the frequencies of Treg cells in different groups. (G) The bar graph shows the statistical frequencies of Th1, Th2, Th17, and Treg cells. *p < 0.05, **p < 0.01.