Additional file 1 of Sialic acid exacerbates gut dysbiosis-associated mastitis through the microbiota-gut-mammary axis by fueling gut microbiota disruption

Additional file 1: Figure S1. SARA induces mastitis in cows. Cows were treated with a standard or high-grain diet for two months and ruminal, serum, milk and mammary gland tissues were harvested for analysis. A. Ruminal PH at day 60 from Health and SARA cows (n=6). B-C. Ruminal and serum LPS levels were detected using ELISA (n=6). D. Somatic cell count was performed in Health and SARA cows (n=6). E. Representative images of H&E-stained sections from Health and SARA samples. Red arrows indicate leukocyte infiltration. Blue arrows show the structure injury of mammary gland. Black arrows indicate edema. F. Histological score based on H&E-stained sections (n=6). Mammary TNF-α (G) and IL-1β (H) from Health and SARA groups were measured by ELISA (n=6). Each dot represents an individual cow (A-D and F-H) and Student’s t test was performed (A-D and F-H). **p < 0.01, ***p < 0.001 indicate significance. Figure S2. Data quality checks. A. The Pearson correlation of ruminal QC samples. B-C. The PCA score plots for Health and SARA samples containing QC samples (n=6). QC, quality control; PCA, Principal component analysis. Figure S3. Classification and functional annotation of metabolites. A. KEGG pathway annotation for Health and SARA ruminal samples. B. HMDB classification annotation. C. Lipid maps annotation for Health and SARA groups. HMDB, Human Metabolome Database; KEGG, Kyoto Encyclopedia of Genes and Genomes. Figure S4. SARA induced ruminal metabolic changes. A. PLS-DA score plots for ruminal samples (n=6). B. Cross-validation plot with a permutation test repeated 200 times. The intercepts of R2 (0.0, 0.57) and Q2 (0.0,–1.09) indicate that the PLS-DA model was not overfitting. C. Pathway enrichment analysis of significantly elevated metabolites in SARA sample according to the KEGG pathway. Figure S5. Spearman correlation between metabolites and inflammatory parameters. The red color denotes a positive correlation, while green color denotes a negative correlation. The intensity of the color is proportional to the strength of Spearman correlation. *p < 0.05, **p < 0.01, ***p < 0.001 indicate significance. Figure S6. Spearman correlation among metabolites. The top 20 correlated metabolites were showed based on the P value. The red color denotes a positive correlation, while blue color denotes a negative correlation. Figure S7. SA and FMT change the intestinal SA levels. A-B. The intestinal SA levels from different treatment groups (n=6-8). Data are expressed as the mean ± SD (A-B) and one-way ANOVA was performed, followed by Tukey test (A-B). *p < 0.05, **p < 0.01, ***p < 0.001 indicate significant difference. Figure S8. Sialic acid treatment has minimum effects on the synthesis of milk proteins and ileum histology. A-D. Relative mammary gene expressions associated with the synthesis of milk proteins from indicated groups, including Csn1, Csn2, Csn3, and Wap (n=7-8). E. The average weight changes of litters from different treatment groups (n=6). F. Representative images of H&E-stained ileum sections from indicated mice. G. Histological score based on H&E-stained sections (n=7-8). Figure S9. Composition of the gut microbiota in different groups. A. Chao1 index in different groups (n=7-8). B. Ace index (n=7-8). C. Bacterial composition at the family level in the gut were displayed (n=7-8). Each dot represents an individual mouse (A and B) and one-way ANOVA was performed, followed by Tukey test (A and B). ***p < 0.001 indicate significance. ns, no significance. Figure S10. Top 50 metabolism pathways enriched in different groups using Tax4Fun. Figure S11. Sodium tungstate treatment reduces intestinal Enterobacteriaceae abundance. A. The gut microbial compositions at the family level from different treatment groups (n=4). B. A Wilcoxon rank-sum test was performed to identify the differential bacterial taxa in the AN and AN+T groups (FDR < 0.05) (n=4). Figure S12. The ruminal and intestinal microbial compositions in the donor and recipient mice, and the effect of RMT on systemic inflammation in mice. A-D. Alpha diversity indices, including observed species (A), Shannon (B), Chao1 (C) and Simpson index (D), from Health and SARA groups (n=6). E. The ruminal microbial compositions at the family level from the indicated groups (n=6). F. Venn diagram showed the observed OTUs in different RMT groups. G-I. Alpha diversity indices, including Shannon (G), Chao1 (H) and Simpson index (I), from different treatment groups (n=7). J. The gut microbial compositions at the family level from different RMT groups (n=7). K-L. Serum TNF-α (K) and IL-1β (L) levels by ELISA (n=7). Data are expressed as boxplot (A-D and G-I) or the mean ± SD (K-L). A Student’s t test (A-D) or one-way ANOVA was performed, followed by Tukey test (G-I and K-L). *p < 0.05, **p < 0.01, ***p < 0.001 indicate significant difference. Figure S13. A high-starch diet promotes SA production and mastitis in SRMT mice. A. Neu5Ac levels from different treatment groups (n=5). B. Representative images of H&E-stained mammary sections. C. Histological scores based on H&E-stained mammary sections (n=5). D-F. Mammary TNF-α (D), IL-1β (E), MPO activity (F) were assessed (n=5). Data are expressed as the mean ± SD (C-F) and one-way ANOVA was performed, followed by Tukey test (C-F). **p < 0.01, ***p < 0.001 indicate significant difference. Table S1. Identified number of differential metabolites in Health and SARA samples. Table S2. Metabolites significantly upregulated in SARA cows and ranked according to the P-value. Table S3. Metabolites significantly downregulated in SARA cows and ranked according to the P-value. Table S4. The oligonucleotides used in this study.