Data_Sheet_1_Modulation of the Caecal Gut Microbiota of Mice by Dietary Supplement Containing Resistant Starch: Impact Is Donor-Dependent.PDF (199.11 kB)
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Data_Sheet_1_Modulation of the Caecal Gut Microbiota of Mice by Dietary Supplement Containing Resistant Starch: Impact Is Donor-Dependent.PDF

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posted on 06.06.2019, 13:48 by Claire Cherbuy, Déborah Bellet, Véronique Robert, Camille Mayeur, Andreas Schwiertz, Philippe Langella

Alterations in the gut microbiota have been associated with a wide range of pathologies and conditions. Maintaining a well-balanced microbiota is a key factor in sustaining good health. Our aim was to investigate the impact of a resistant starch-containing dietary supplement (SymbioIntest®) on the composition of the human gut microbiota and on intestinal short chain fatty acid (SCFA) concentration. Human microbiota-associated mice were used. Ex-germ-free mice were inoculated with fecal suspensions from four different donors. Three weeks later, the mice were orally gavaged for 1 month with either a daily dose of 10 mg of SymbioIntest® or the vehicle (water) for the negative control group. The composition of the microbiota and SCFA levels were analyzed by 16S rRNA gene sequencing and gas chromatography, respectively. In three groups of mice, SymbioIntest® supplementation increased the concentration of caecal butyrate. This was in conjunction with a remodeling of the gut microbiota. OTUs belonging to the Bacteroidaceae, Porphyromonadaceae, Lachnospiraceae and Ruminococcaceae families were affected. In two groups of mice the greatest changes in OTUs were seen in the Faecalibacterium genus. The supplementation’s highest impact was observed in mice inoculated with gut microbiota containing a lower number of Ruminococcaceae and Faecalibacterium and a higher number of Prevotellaceae. SymbioIntest® supplementation elicited a beneficial effect on the healthy adult gut microbiota by increasing caecal butyrate production and health-promoting taxa. We highlight the fact that screening the gut microbiota may be used for predicting individualized responses to dietary interventions and thus developing personalized nutritional strategies.

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