Fig 1.
Diversity of gut bacteria shifts with time.
(A), Experimental design and procedures. (B-C), Body weight and food intake shift with time (n = 6). (D-E), Chao 1 and Simpson indices were plotted to evaluate and compare α-diversity (n = 6). For boxplot with the same letter, the difference is not statistically significant. For boxplot with different letters, the difference is statistically significant. (F-G), Principal coordinate analysis and constrained principal coordinate analysis were plotted to evaluate and compare β-diversity (n = 6). (H), Hierarchical clustering using weighted UniFrac distances. OTU abundance levels were used to construct the heatmap (n = 6). Letters A-J represent the 7th week to 15th week, and numbers 1–6 represent six rats. Data were represented as means ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001.
Fig 2.
Gut bacteria composition at the phylum level.
(A-B), Gut bacterial composition at the phylum level was compared for each sample and each group (n = 6). (C-E), The relative abundance of Firmicutes and Bacteroides shifted with time (n = 6), and the Firmicutes:Bacteroides ratio shifted with time (n = 6). For boxplot with the same letter, the difference is not statistically significant. For boxplot with different letters, the difference is statistically significant. (F), Spearman correlation between body weight and the Firmicutes:Bacteroides ratio (n = 54).
Fig 3.
Gut bacteria composition at the genus level.
(A-B), Gut bacterial composition at the genus level was compared for each sample and each group (n = 6). (C-L), Certain genera shifted with time (ANOVA test followed by post-hoc tests, n = 6).
Fig 4.
Gut inflammation, bone metabolism and gut barrier permeability-related cytokine expression in sexually mature rats.
(A-G), Levels of inflammation-associated cytokines were measured in fecal samples (n = 6). (H-I), Levels of gut barrier permeability-associated cytokines were measured in fecal samples (n = 6). Data were represented as means ± SEM. ns, no significance.
Fig 5.
Spearman correlation between gut bacteria and gut inflammation.
(A), Spearman correlation between gut bacteria and gut inflammation and gut barrier permeability-related cytokine expression in the 7th week. (B), Spearman correlation between gut bacteria and gut inflammation and gut barrier permeability-related cytokine expression in the 15th week. Note: *P < 0.05, **P < 0.01, ***P < 0.001.
Fig 6.
Bacterial gene function annotation and phenotype prediction.
(A-B), Anaerobic and potentially pathogenic shifts with time are shown. (C-K), The average abundance of differentially enriched KEGG pathways (ANOVA test followed by post-hoc tests).