Additional file 1 of Dietary fibers boost gut microbiota-produced B vitamin pool and alter host immune landscape
Creators: name: Grant, Erica T.
name: Parrish, Amy
name: Boudaud, Marie
name: Hunewald, Oliver
name: Hirayama, Akiyoshi
name: Ollert, Markus
name: Fukuda, Shinji
name: Desai, Mahesh S.
Publisher: name: figshare
Year: 2024
Subjects: subject: Immunology
subject: FOS: Clinical medicine

description: Supplementary Material 1: Supplementary Figure 1. Annotated cluster heatmap of colonic lamina propria (cLP) analysis. CD45+ single live cells were imported into R for FlowSOM analysis. Based on the expression of 26 markers columns), 100 clusters were generated and manually merged based on marker expression (columns) to form 30 biologically relevant cell populations (rows). Percentages in parentheses next to the population name represent the percentage of that population among CD45+ cells. Marker expression is normalized between 0 and 1. Supplementary Figure 2. CyTOF analysis reveals systemic immune changes from a fiber-free diet. a) UMAP visualization of CD45+ immune cells isolated from the spleens of SPF (top) and GF (bottom) mice, alongside the markers used to elucidate main cell subsets (all groups pooled). c) Select marker expression facetted by colonization state and diet. Samples within each group were downsampled and then concatenated such that 60,000 events were analyzed per group (420,000 total). c) Splenic immune cell populations significantly different between specific-pathogen-free (SPF) mice fed a standard chow 1 (SC1), standard chow 2 (SC2), inulin-supplemented (IN), fiber-supplemented (FS) or fiber-free (FF) diet, alongside germ-free (GF) mice fed an SC1 or FF diet, represented as % of total CD45+ cells. Statistical testing was performed using Brown-Forsythe and Welch ANOVA or Kruskal-Wallis test with P values adjusted using the Benjamini–Hochberg method. n=4 (SPF SC1), 8 (SC2, IN, FS; 2 batches of 3–4 mice), 5 (SPF FF), or 6–7 (GF SC1, GF FF; 2 batches of 3–4 mice) mice per group. Only populations with significant differences between the diets are shown; see Supplementary Table 4 for complete list of populations analyzed. For SC2 and FS, one sample per diet was not analyzed by CyTOF due to low viable cell count; for IN, one sample (In4) was excluded from subsequent analyses due to low event count. Supplementary Figure 3. CyTOF analysis reveals pulmonary immune changes from a fiber-free diet. a) UMAP visualization of CD45+ immune cells isolated from the lungs of SPF (top) and GF (bottom) mice, alongside the markers used to elucidate main cell subsets (all groups pooled). c) Select marker expression facetted by colonization state and diet. Samples within each group were downsampled and then concatenated such that 100,000 events were analyzed per group (400,000 total). c) Pulmonary immune cell populations significantly different between specific-pathogen-free (SPF) mice fed a standard chow 1 (SC1) or fiber-free (FF) diet, alongside germ-free (GF) mice fed an SC1 or FF diet, represented as % of total CD45+ cells. Statistical testing was performed using Brown-Forsythe and Welch ANOVA or Kruskal-Wallis test with P values adjusted using the Benjamini–Hochberg method. n=5 (SPF SC1, SPF FF) or 3 (GF SC1, GF FF) mice per group. Only populations with significant differences between the diets are shown; see Supplementary Table 5 for complete list of populations analyzed. Supplementary Figure 4. Comparison of serum and cecal metabolomes across diets. a) Venn diagrams and UpSet plot representing intersecting sets of metabolites present in serum and cecal contents of specific-pathogen-free (SPF) mice fed all diets: standard chow 1 (SC1), standard chow 2 (SC2), inulin-supplemented (IN), fiber-supplemented (FS) or fiber-free (FF). b) PCA of serum metabolomes with loadings overlain for the top 20 metabolites contributing to PC1 and PC2. Ellipses represent 95% CI. c) Heatmap of the 38 differentially abundant serum metabolites in SPF mice fed each diet according to a linear mixed-effect model with the GF FF group as reference. Concentrations were normalized by volume, log-transformed, then scaled for each metabolite by mean-centering and dividing by the standard deviation. Metabolite order is based on Ward clustering; sample order is fixed by group. d) Serum concentrations of primary bile acids taurocholate and free bile acid cholate. e) Cecum concentrations of primary bile acids taurocholate and glycocholate, free bile acid cholate, and secondary bile acid deoxycholate. One-way ANOVA with adjusted P values calculated using the Benjamini–Hochberg method. n=4 mice per group (one outlier removed from FF group based on PCA), mean ± SD. Different letters denote statistically significant differences (adjusted P&lt;0.01). Standard chow 1 (SC1)=green, standard chow 2 (SC2)=brown, inulin-supplemented (IN)=purple, fiber-supplemented (FS)=blue, fiber-free (FF)=red. Supplementary Figure 5. Cecal metabolome of germ-free mice is less perturbed by diet. a) Venn diagrams and UpSet plot representing intersecting sets of metabolites present in cecal contents of specific-pathogen-free (SPF), gnotobiotic (14SM), and germ-free (GF) mice fed a standard chow 1 (SC1) or fiber-free (FF) diet. b) PCA of cecal metabolomes of GF and 14SM mice fed an SC1 or FF diet with loadings overlain for the top 20 metabolites contributing to PC1 and PC2. Ellipses represent 95% CI. c) Heatmap of top 50 differentially abundant cecal metabolites in GF and 14SM mice fed an SC1 or FF diet according to a linear mixed-effect model with the GF FF group as reference. Metabolite concentrations were normalized to the cecal weight, log-transformed, then scaled for each metabolite by mean-centering and dividing by the standard deviation. Metabolite order is based on Ward clustering; sample order is fixed by group. n=4 mice per group (one outlier removed from SPF FF group based on PCA). Standard chow 1 (SC1)=green, fiber-free (FF)=red, 14SM=open squares, GF=open circles. Supplementary Figure 6. Bacterial contributors to vitamin B1, B2, and B5 metabolism in the cecum. a) Predicted community composition based on metatranscriptome using MetaPhlan 3 within HUMAnN 3. b) Stratified abundance of enzymes immediately upstream of thiamine phosphate and thiamine pyrophosphate (vitamin B1 precursors). TMPase is produced by the host, therefore all bacterial transcripts shown here correspond to enzymes that contribute to thiamine availability. c) Stratified abundance of enzymes involved in nicotinate (vitamin B3) synthesis. d) Stratified abundance of enzymes immediately up and downstream of pantothenate (vitamin B5). n=4 mice per group, error bars represent SD. Supplementary Figure 7. Bacterial contributors to vitamin B6, B7, B9 and B12 metabolism in the cecum. a) Stratified abundance of enzymes immediately upstream of pyridoxine, pyridoxamine, and pyridoxal and their phosphorylated derivatives (vitamin B6). b) Stratified abundance of enzymes immediately up and downstream of biotin (vitamin B7). c) Stratified abundance of enzymes immediately upstream of folate (vitamin B9). d) Stratified abundance of enzymes immediately upstream of cobalamin (vitamin B12). n=4 mice per group, error bars represent SD.