Transmissible microbial and metabolomic remodeling by soluble dietary fiber improves metabolic homeostasis

Baokun He, Kazunari Nohara, Nadim J Ajami, Ryan D Michalek, Xiangjun Tian, Matthew Wong, Susan H Losee-Olson, Joseph F Petrosino, Seung-Hee Yoo, Kazuhiro Shimomura, Zheng Chen, Baokun He, Kazunari Nohara, Nadim J Ajami, Ryan D Michalek, Xiangjun Tian, Matthew Wong, Susan H Losee-Olson, Joseph F Petrosino, Seung-Hee Yoo, Kazuhiro Shimomura, Zheng Chen

Abstract

Dietary fibers are increasingly appreciated as beneficial nutritional components. However, a requisite role of gut microbiota in fiber function and the overall impact of fibers on metabolomic flux remain unclear. We herein showed enhancing effects of a soluble resistant maltodextrin (RM) on glucose homeostasis in mouse metabolic disease models. Remarkably, fecal microbiota transplantation (FMT) caused pronounced and time-dependent improvement in glucose tolerance in RM recipient mice, indicating a causal relationship between microbial remodeling and metabolic efficacy. Microbial 16S sequencing revealed transmissible taxonomic changes correlated with improved metabolism, notably enrichment of probiotics and reduction of Alistipes and Bacteroides known to associate with high fat/protein diets. Metabolomic profiling further illustrated broad changes, including enrichment of phenylpropionates and decreases in key intermediates of glucose utilization, cholesterol biosynthesis and amino acid fermentation. These studies elucidate beneficial roles of RM-dependent microbial remodeling in metabolic homeostasis, and showcase prevalent health-promoting potentials of dietary fibers.

Figures

Figure 1. RM improves energy homeostasis and…
Figure 1. RM improves energy homeostasis and alters gut microbiota in db/db mice.
Fasting glucose (a), oral glucose tolerance test (OGTT) (b) and insulin tolerance test (ITT) (c) showed improvements in db/db mice after 8 weeks of RM treatment relative to Ctrl (n = 7-8). Area under curve (AUC) values are also shown for GTT and ITT. Values are presented as means ± SEM. *p < 0.05, **p < 0.01. For microbial sequencing analysis, alpha-diversity plots of gut microbiota (d) and heat maps of relative abundance of OTUs (as percentage of total microbiota) (e) are shown for db/db mice treated for 8 weeks with Ctrl or RM (n = 4-5). Level 2 (phylum) and 6 (genus) are shown. P values for diversity plots were calculated by 2-way ANOVA (repeated measure) to be Chao1 (P = 0.62) or Shannon (P = 0.59). See Supplementary Tables 1 and 2 for numerical values for heat maps in (e).
Figure 2. Fecal microbiota from donor db/db…
Figure 2. Fecal microbiota from donor db/db mice confers metabolic benefits of RM in recipient db/db mice.
(a) Alpha-diversity plots showed depletion of gut microbiota by antibiotics treatment in recipient mice prior to fecal microbiota transplantation. P values were calculated by 2-way ANOVA (repeat measure) to be Chao1 (P < 0.0001) or Shannon (P < 0.0001). Fasting glucose (b) and oral glucose tolerance test (OGTT) (c) in recipient db/db mice before (0 month) and after transplantation (1, 2 and 3 months) of fecal microbiota from donor mice (n = 6). Area under curve (AUC) values are also shown. Values are presented as means ± SEM. *p < 0.05, **p < 0.01.
Figure 3. Transmissible remodeling of gut microbiota…
Figure 3. Transmissible remodeling of gut microbiota in recipient db/db mice after fecal microbiota transplantation.
Alpha-diversity plots (a), heat maps of average (b) and time-resolved (c) abundance of phylum- and genus-level OTUs calculated as percentage of total microbiota in recipient db/db mice (n = 6) are shown. Values are presented as means ± SEM. P values for diversity plots were calculated by 2-way ANOVA (repeated measure) to be Chao1 (P = 0.014) or Shannon (P = 0.086). See Supplementary Tables 5 and 6 for numerical values for heat maps.
Figure 4. RM alters fecal metabolomic profiles…
Figure 4. RM alters fecal metabolomic profiles in donor and recipient db/db mice.
(a) Numbers of fecal metabolites affected, either up- or down-regulated (p < 0.05), by RM in donor and recipient mice (n = 6). Venn diagrams showing the overlaps between donor and recipient samples are also shown. (b) Principal component analysis of fecal metabolites affected by RM in donor and recipient mice (n = 6). (c) Hierarchical clustering heat map showing a predominant effect of RM on the relative abundance of the fecal metabolites such that RM donor and RM recipient mice (dRM and rRM), as well as Ctrl donor and Ctrl recipient (dCtrl and rCtrl), are clustered together (n = 6). Color bar values correspond to relative abundance measured in metabolomic analysis. Note that the color scheme is different from that for the heat maps showing microbial changes. (d) Random forest analysis showing a unique metabolomic signature between Ctrl and RM fecal samples, preserved in both donors and recipients, with a predictive accuracy of 96% in differentiating between the Ctrl and RM groups (n = 6).
Figure 5. RM alters metabolites involving in…
Figure 5. RM alters metabolites involving in glucose metabolism of gut microbiota in donor and recipient mice.
(a) Schematic of the glucose metabolism pathway. Metabolites decreased by RM treatment in the feces of donor or recipient db/db mice are highlighted in green whereas metabolites not detected or unchanged are marked in black or grey. (b) Graphs showing relative abundance of metabolites affected by RM treatment in the feces of donor or recipient db/db mice (n = 6). Values are presented as means ± SEM.
Figure 6. RM alters metabolites involving in…
Figure 6. RM alters metabolites involving in cholesterol metabolism of gut microbiota in donor and recipient mice.
(a) Schematic of the cholesterol metabolic pathway. Metabolites decreased by RM treatment in the feces of donor or recipient db/db mice are highlighted in green whereas metabolites not detected or unchanged are marked in black. (b) Graphs showing relative abundance of metabolites affected by RM treatment in the feces of donor or recipient db/db mice (n = 6). Values are presented as means ± SEM.

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