An interventional Soylent diet increases the Bacteroidetes to Firmicutes ratio in human gut microbiome communities: a randomized controlled trial

Our knowledge of the relationship between the gut microbiome and health has rapidly expanded in recent years. Diet has been shown to have causative effects on microbiome composition, which can have subsequent implications on health. Soylent 2.0 is a liquid meal replacement drink that satisfies 20% of all nutritional daily recommended values per serving. This study aims to characterize the changes in gut microbiota composition resulting from a short-term Soylent 2.0 liquid diet. Fourteen participants were separated into two groups: 5 in the regular diet group and 9 in the Soylent diet group. The regular diet group maintained a diet closely resembling self-reported regular diets. Participants in the Soylent diet group underwent three dietary phases: A) a regular diet for 2 days, B) five servings of Soylent 2.0 per day and water for 4 days, and C) a regular diet for 4 days. Daily logs reporting diet, bristol stool ratings, and any abdominal discomfort were electronically submitted. Eight fecal samples per participant were collected using fecal sampling kits, which were subsequently sent to uBiome, Inc. for sample processing and V4 16S rDNA sequencing. Reads were clustered into operational taxonomic units (OTUs) and taxonomically identified against the GreenGenes 16S database. We find that an individual’s alpha-diversity is not significantly altered during an all-Soylent diet. In addition, principal coordinate analysis using the unweighted UniFrac distance metric shows samples cluster strongly by individual and not by dietary phase. We also find a significant increase in the ratio of Bacteroidetes to Firmicutes abundance, which is associated with several positive health outcomes, including reduced risk of obesity and intestinal inflammation. Future studies can evaluate the effects of similar meal replacements on the gut microbiome and incorporate additional measurements such as transcriptomics and metagenomics to resolve functional data.