High-dose saccharin supplementation does not induce gut microbiota changes or glucose intolerance in healthy humans and mice

Abstract

Background: Non-caloric artificial sweeteners (NCAS) are widely used as a substitute for dietary sugars to control body weight or glycemia. Paradoxically, some interventional studies in humans and rodents have shown unfavorable changes in glucose homeostasis in response to NCAS consumption. The causative mechanisms are largely unknown, but adverse changes in gut microbiota have been proposed to mediate these effects. These findings have raised concerns about NCAS safety and called into question their broad use, but further physiological and dietary considerations must be first addressed before these results are generalized. We also reasoned that, since NCAS are bona fide ligands for sweet taste receptors (STRs) expressed in the intestine, some metabolic effects associated with NCAS use could be attributed to a common mechanism involving the host.

Results: We conducted a double-blind, placebo-controlled, parallel arm study exploring the effects of pure saccharin compound on gut microbiota and glucose tolerance in healthy men and women. Participants were randomized to placebo, saccharin, lactisole (STR inhibitor), or saccharin with lactisole administered in capsules twice daily to achieve the maximum acceptable daily intake for 2 weeks. In parallel, we performed a 10-week study administering pure saccharin at a high dose in the drinking water of chow-fed mice with genetic ablation of STRs (T1R2-KO) and wild-type (WT) littermate controls. In humans and mice, none of the interventions affected glucose or hormonal responses to an oral glucose tolerance test (OGTT) or glucose absorption in mice. Similarly, pure saccharin supplementation did not alter microbial diversity or composition at any taxonomic level in humans and mice alike. No treatment effects were also noted in readouts of microbial activity such as fecal metabolites or short-chain fatty acids (SCFA). However, compared to WT, T1R2-KO mice were protected from age-dependent increases in fecal SCFA and the development of glucose intolerance.

Conclusions: Short-term saccharin consumption at maximum acceptable levels is not sufficient to alter gut microbiota or induce glucose intolerance in apparently healthy humans and mice.

Trial registration: Trial registration number NCT03032640 , registered on January 26, 2017. Video abstract.

Keywords: Artificial sweeteners; Dysbiosis; Fecal metabolomics; Glucose intolerance; Gut microbiota; Saccharin; Short-chain fatty acids; Sweet taste receptors; T1R2.

Fig. 1

Effects of saccharin and/or lactisole treatment on glucose tolerance in humans. Plasma excursions of a glucose, b insulin, c C-peptide, d glucagon, and e GLP-1 in response to an oral glucose challenge after 2 weeks of treatment (n = 10–13/group). Two-way ANOVA repeated measures, p value of time x treatment effect

Fig. 2

Effects of saccharin treatment on glucose homeostasis in mice. a Glucose responses during an i.g.GTT expressed as area under curve (AUC) before 0 week, 2 and 10 weeks after water or saccharin treatment in WT and T1R2-KO (T1R2) mice. Two-way ANOVA main genotype effect, p < 0.0001; p values of post hoc test. b Glucose excursions during an i.g.GTT after 10 weeks of water or saccharin treatment. Two-way ANOVA repeated measures, p value of main genotype effect. c Ex vivo glucose flux using 3-O-methy-glucose (3-OMG) in intact mouse intestines following 10 weeks of water or saccharin treatment. Two-way ANOVA, p value of main genotype effect. d Ex vivo intestinal permeability assessed by FITC-dextran (4 kDa) flux in intact mouse intestines following 10 weeks of water or saccharin treatment. Two-way ANOVA, p value of main treatment effect. For mouse in vivo studies (n = 23–28/group), for ex vivo studies (n = 6–11/group)

Fig. 3

Treatment effects on gut microbial diversity and composition (genus) in humans. a Alpha diversity indices (Chao1, Shannon, and Simpson) pre- and post-treatment (lines connect data from the same participant; detailed statistics, Supp. Table.3). b Nonmetric multidimensional scaling (NMDS) plots of Bray-Curtis dissimilarities between all groups pre- and post-treatment, or c within each treatment group (lines connect data from the same participant). d Within-subject Bray-Curtis dissimilarity (paired pre-post) for each treatment group (detailed statistics of beta diversity, Supp. Table.4). e Average values (arbitrary units) of pre-post compositional changes (Δ) at the genus level for each treatment (detailed statistics, Supp. Table.5). For a, two-way ANOVA repeated measures, p value of time x treatment effect. For b, c, PERMANOVA p value. For d, ANOVA p value

Fig. 4

Treatment effects on gut microbial diversity and composition (genus) in mice. a Alpha diversity indices (Chao1, Shannon, and Simpson) pre- and post-treatment (lines connect data from the same mouse; detailed statistics, Supp. Table.7). b Nonmetric multidimensional scaling (NMDS) plots of Bray-Curtis dissimilarities between all groups pre- and post-treatment, or c within each group (lines connect data from the same participant). d Within-subject Bray-Curtis dissimilarity (paired pre-post) for each treatment group (detailed statistics of beta diversity, Supp. Table.8). e Average values (arbitrary units) of pre-post compositional changes (Δ) at the genus level for each treatment (detailed statistics, Supp. Table.9). For a, two-way ANOVA repeated measures, p value of time x treatment effect. For b, c, PERMANOVA p value. For d, Kruskal-Wallis p value. W water, S saccharin

Fig. 5

Treatment effects on fecal metabolomics in humans and mice. a Pre-post treatment variation in fecal metabolites within each treatment group in humans and b in mice using orthogonal partial least squares discriminant analyses (OPLS-DA). c Statistical significance (-log(p)) of pre-post treatment differences (Δ) in NMR spectral bins (ppm) of fecal metabolites in mice. In blue, NMR spectral bins assigned to saccharin. Dotted horizontal line shows statistically significance for the FDR-corrected p value. d Presence of saccharin in mouse and e human post-treatment fecal samples. Dashed lines represent average noise ± SD (detection threshold). f Assessment of short-chain fatty acids (SCFA) in human fecal samples post treatment. h SCFA in mouse fecal samples pre- and post-treatment (n = 8/group). For (a, b), R2; Q2; and CV-ANOVA p value. For f, one-way ANCOVA p value, pre-treatment as covariate. For h, two-way ANOVA repeated measures with post hoc p value. W water, S saccharin