Stool energy density is positively correlated to intestinal transit time and related to microbial enterotypes

Abstract

Background

It has been hypothesised that the gut microbiota causally affects obesity via its capacity to extract energy from the diet. Yet, evidence elucidating the role of particular human microbial community structures and determinants of microbiota-dependent energy harvest is lacking.

Results

Here, we investigated whether energy extraction from the diet in 85 overweight adults, estimated by dry stool energy density, was associated with intestinal transit time and variations in microbial community diversity and overall structure stratified as enterotypes. We hypothesised that a slower intestinal transit would allow for more energy extraction. However, opposite of what we expected, the stool energy density was positively associated with intestinal transit time. Stratifications into enterotypes showed that individuals with a Bacteroides enterotype (B-type) had significantly lower stool energy density, shorter intestinal transit times, and lower alpha-diversity compared to individuals with a Ruminococcaceae enterotype (R-type). The Prevotella (P-type) individuals appeared in between the B- and R-type. The differences in stool energy density between enterotypes were not explained by differences in habitual diet, intake of dietary fibre or faecal bacterial cell counts. However, the R-type individuals showed higher urinary and faecal levels of microbial-derived proteolytic metabolites compared to the B-type, suggesting increased colonic proteolysis in the R-type individuals. This could imply a less effective colonic energy extraction in the R-type individuals compared to the B-type individuals. Notably, the R-type had significantly lower body weight compared to the B-type.

Conclusions

Our findings suggest that gut microbial energy harvest is diversified among individuals by intestinal transit time and associated gut microbiome ecosystem variations. A better understanding of these associations could support the development of personalised nutrition and improved weight-loss strategies.

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