Infusion of donor feces affects the gut-brain axis in humans with metabolic syndrome

Abstract

Objective: Increasing evidence indicates that intestinal microbiota play a role in diverse metabolic processes via intestinal butyrate production. Human bariatric surgery data suggest that the gut-brain axis is also involved in this process, but the underlying mechanisms remain unknown.

Methods: We compared the effect of fecal microbiota transfer (FMT) from post-Roux-en-Y gastric bypass (RYGB) donors vs oral butyrate supplementation on (¹²³I-FP-CIT-determined) brain dopamine transporter (DAT) and serotonin transporter (SERT) binding as well as stable isotope-determined insulin sensitivity at baseline and after 4 weeks in 24 male and female treatment-naïve metabolic syndrome subjects. Plasma metabolites and fecal microbiota were also determined at these time points.

Results: We observed an increase in brain DAT after donor FMT compared to oral butyrate that reduced this binding. However, no effect on body weight and insulin sensitivity was demonstrated after post-RYGB donor feces transfer in humans with metabolic syndrome. Increases in fecal levels of Bacteroides uniformis were significantly associated with an increase in DAT, whereas increases in Prevotella spp. showed an inverse association. Changes in the plasma metabolites glycine, betaine, methionine, and lysine (associated with the S-adenosylmethionine cycle) were also associated with altered striatal DAT expression.

Conclusions: Although more and larger studies are needed, our data suggest a potential gut microbiota-driven modulation of brain dopamine and serotonin transporters in human subjects with obese metabolic syndrome. These data also suggest the presence of a gut-brain axis in humans that can be modulated.

Ntr registration: 4488.

Keywords: Gut-brain axis; Gutmicrobiota; Metabolites; Obesity.

Figure 1

A. Brain SPECT image and ROIs. The top panel shows a representative example of a brain MRI overlaid with a brain SPECT image obtained 2 h after the intravenous administration of the radioligand ¹²³I-FP-CIT. In the bottom panel, the regions of interest (ROIs) for specific parts of the human brain are shown, which were subsequently used to determine SERT binding in the thalamus and hypothalamus and DAT binding in the striatum. B, C, and D. Changes in striatal DAT as well as SERT binding in thalamus and hypothalamus. Changes in DAT and SERT binding between group comparisons showed that striatal DAT-binding ratios decreased in the butyrate group and increased in the FMT group, resulting in a significant change over time between both groups, while for SERT binding, a trend was observed. ∗p < 0.05.

Figure 2

Changes in fecal microbiota composition after butyrate supplementation or allogenic FMT. (A) Biplot of redundancy analysis (RDA axis 1 vs axis 2) of fecal microbiota data constrained by butyrate vs allogenic FMT treatment variables (before, baseline, and 4 weeks after treatment). Baseline fecal microbiota composition in the post-RYBG feces donors is also shown. (B) Biplot of deltas from the top 10 amplicon sequence variant (ASV) markers of fecal microbiota after allogenic FMT and butyrate treatment. AUC = 0.83 ± 0.29. (C) Spider plot depicting a panel of bacterial species that significantly differentiated between the 2 different treatment groups based on changes in the fecal microbiota composition. The axis reflects the amount of change in % of the bacterial species after either treatment.

Figure 3

Gut microbiota composition. Gut microbiota composition at phylum (A), family (B), genus (C), and species (D) levels stratified by time and group of subjects.

Figure 4

Changes in plasma metabolites. Biplot of redundancy analysis (RDA axis 1 vs axis 2) of the plasma metabolite data constrained by butyrate and allogenic FMT treatment variables (before, baseline, and 4 weeks after treatment). Baseline plasma metabolites in the post-RYBG feces donors is also shown. The brackets on the axis labels refer to the proportion of the constrained variance explained by the respective axis/RDAs. In this case, the constrained variance was 7.8% of the total variance.

Figure 5

Correlations between changes in gut microbiota and striatal DAT binding. (A) Allogenic post-RYGB FMT donor group (left panel: Spearman's correlation values, right panel: p values). Changes in Prevotella copri correlated inversely with changes in DAT binding (rho = −0.50, p value = 0.1). (B) Butyrate intervention group (left panel: Spearman's correlation values; right panel: p values). Changes in Bacteroides uniformis positively correlated with changes in DAT binding (rho = 0.70, p value = 0.02).

Figure 6

Correlations between changes in plasma metabolites and change in striatal DAT binding. (A) Allogenic post-RYGB FMT donor group (left panel: Spearman's correlation values, right panel: p values). Changes in betaine and glycine correlated positively with change in DAT without reaching significance. (B) Butyrate intervention group (left panel: Spearman's correlation values, right panel: p values). All 4 metabolites correlated positively with changes in DAT with glycine (rho = 0.61, p value = 0.05) and lysine (rho = 0.63, p value = 0.04).

Figure 7

Correlations between changes in plasma metabolites and gut microbiota. (A) Allogenic post-RYGB FMT donor group (left panel: Spearman's correlation values, right panel: p values). Bacteroides uniformis correlated negatively with all 4 metabolites with betaine (rho = −0.61, p value = 0.03) and lysine (rho = 0.8, p value = 0.001). (B) Butyrate intervention group (left panel: Spearman's correlation values, right panel: p values). Bacteroides uniformis correlated significantly with plasma glycine, betaine, and lysine (p = 0.01, p = 0.04, and p = 0.03) and a positive trend was observed with Prevotella copri.