Additional file 2 of Effects of caloric restriction on the gut microbiome are linked with immune senescence

Additional file 1: Supplementary Figure 1. Related to Fig. 1. MMSP50 is a representative donor of the weight loss cohort. A Examination of baseline alpha diversity demonstrates that MMSP50 is at the 54th ranked percentile for baseline diversity after VLCD. B Their baseline microbiota composition (principal coordinates analysis of Bray-Curtis Dissimilarity) is well within the 95% confidence interval of baseline composition for the cohort (dotted line) and C their change in community structure is the 19th percentile for change in composition. Supplementary Figure 2. Related to Fig. 2. No significant changes in energy loss or fecal content after microbial colonization. Metabolic analysis of germ-free (GF) mice and mice inoculated with the AdLib and CalRes human gut microbiota. A-D Energy loss (A), fecal energy content (B), food consumption (C), and energy absorption (D) were measured using bomb calorimetry in GF and colonized mice. E Body weights in g. ** P < 0.01, *** P < 0.001 as determined using 2-way ANOVA with Bonferonni’s post-test correction for multiple comparisons. error bars = SEM. Supplementary Figure 3. Related to Fig. 3. Differential expression of surface markers in different colonic immune cell clusters of germ-free and colonized mice. A The heatmap shows differentially distributed colonic immune cell phenotypes quantified by PhenoGraph clustering. The distribution of each cell cluster (rows) is shown for each murine sample (columns). B The heatmap shows the distribution of colonic immune lineages based on the expression of canonical lineage markers by t-SNE on all colonic viable CD45+ leukocytes. The differential expression of each selected surface marker (rows) is shown for each immune cell cluster (columns). The significance levels of the comparison between the groups for each immune cell cluster are depicted by semi-supervised hierarchical clustering. The top bubbles denote clusters with significantly different abundances between the groups. Bubble colors indicate the one of the two groups being compared with higher average cellular frequencies; bubble size indicates the -log2 FDR-adjusted p-values. Visualization of all colonic viable CD45+ leukocytes by t-SNE. Overlayed colors represent Phenograph clusters as defined in heatmap. C-G Absolute numbers of colonic leukocytes (C), CD4+ T cells (D), CD8+ T cells (E), B cells (F), and NK cells (G) defined by manual gating of mass cytometry data, from germ-free (GF) mice and mice colonized with the AdLib and CalRes human gut microbiota from the top weight loser of an 8-week weight loss intervention study (n=9 or more mice per group). * P<0.05, ANOVA with Bonferonni’s post-test correction for multiple comparison. Supplementary Figure 4. Related to Fig. 4. Differential expression of surface markers in different splenic immune cell clusters of germ-free and colonized mice. A The heatmap shows differentially distributed splenic immune cell phenotypes quantified by PhenoGraph clustering. The distribution of each cell cluster (rows) is shown for each murine sample (columns). B The heatmap shows the distribution of splenic immune lineages based on the expression of canonical lineage markers by t-SNE on all colonic viable CD45+ leukocytes. The differential expression of each selected surface marker (rows) is shown for each immune cell cluster (columns). The significance levels of the comparison between the groups for each immune cell cluster are depicted by semi-supervised hierarchical clustering. The top bubbles denote clusters with significantly different abundances between the groups. Bubble colors indicate the one of the two groups being compared with higher average cellular frequencies; bubble size indicates the -log2 FDR-adjusted p-values. Visualization of all splenic viable CD45+ leukocytes by t-SNE. Overlayed colors represent Phenograph clusters as defined in heatmap. C-G Absolute numbers of splenic leukocytes (C), CD4+ T cells (D), CD8+ T cells (E), B cells (F), and NK cells (G) defined by manual gating of mass cytometry data, from germ-free (GF) mice and mice colonized with the AdLib and CalRes human gut microbiota from the top weight loser of an 8-week weight loss intervention study (n=9 or more mice per group). * P<0.05, ANOVA with Bonferonni’s post-test correction for multiple comparison. Supplementary Figure 5. Related to Fig. 5. Differential expression of surface markers in different hepatic immune cell clusters of germ-free and colonized mice. A The heatmap shows differentially distributed hepatic immune cell phenotypes quantified by PhenoGraph clustering. The distribution of each cell cluster (rows) is shown for each murine sample (columns). B The heatmap shows the distribution of hepatic immune lineages based on the expression of canonical lineage markers by t-SNE on all colonic viable CD45+ leukocytes. The differential expression of each selected surface marker (rows) is shown for each immune cell cluster (columns). The significance levels of the comparison between the groups for each immune cell cluster are depicted by semi-supervised hierarchical clustering. The top bubbles denote clusters with significantly different abundances between the groups. Bubble colors indicate the one of the two groups being compared with higher average cellular frequencies; bubble size indicates the -log2 FDR-adjusted p-values. Visualization of all hepatic viable CD45+ leukocytes by t-SNE. Overlayed colors represent Phenograph clusters as defined in heatmap. C-G Absolute numbers of hepatic leukocytes (C), CD4+ T cells (D), CD8+ T cells (E), B cells (F), and NK cells (G) defined by manual gating of mass cytometry data, from germ-free (GF) mice and mice colonized with the AdLib and CalRes human gut microbiota from the top weight loser of an 8-week weight loss intervention study (n=9 or more mice per group). ANOVA with Bonferonni’s post-test correction for multiple comparison. Supplementary Figure 6. Related to Fig. 6. Gut microbial community structure slightly affects composition and activation of liver immune cells. The heatmap shows latent correlation matrix between abundances of amplicon sequence variants (ASVs) detected in stool samples and all immune parameters analyzed in liver of mice 21 days after inoculation with AdLib and CalRes human gut microbiota. Immune parameters are expressed as frequencies, i.e., percent of parent, except those labeled # which were quantified as absolute cell counts. Heatmap was ordered according to rows and columns first principal components to highlight the cross-correlation structure. Asterisks indicate variables that were selected in L1-penalized sparse canonical correlation analysis (CCA). Circular chord plots display latent correlation between frequencies of manually defined immune subsets and L1-selected ASVs including the top ten taxa that either positively or negatively associate with the immunological dataset. Blue to red colour scale in heatmap and chords indicates negative and positive correlation values. Color of row-legend bar and species labels denotes the phylum level. Colors of column legend bars indicate parental lineage and differentiation level (antigen-experience) of lymphocyte subsets, respectively. The boxplot inset shows how experimental groups as a latent variable are not well-explained by the sparse canonical covariate.