Functional heterogeneity in the fermentation capabilities of the healthy human gut microbiota

PLoS One. 2021 Jul 21;16(7):e0254004. doi: 10.1371/journal.pone.0254004. eCollection 2021.

Abstract

The human gut microbiota is known for its highly heterogeneous composition across different individuals. However, relatively little is known about functional differences in its ability to ferment complex polysaccharides. Through ex vivo measurements from healthy human donors, we show that individuals vary markedly in their microbial metabolic phenotypes (MMPs), mirroring differences in their microbiota composition, and resulting in the production of different quantities and proportions of Short Chain Fatty Acids (SCFAs) from the same inputs. We also show that aspects of these MMPs can be predicted from composition using 16S rRNA sequencing. From experiments performed using the same dietary fibers in vivo, we demonstrate that an ingested bolus of fiber is almost entirely consumed by the microbiota upon passage. We leverage our ex vivo data to construct a model of SCFA production and absorption in vivo, and argue that inter-individual differences in quantities of absorbed SCFA are directly related to differences in production. Though in vivo studies are required to confirm these data in the context of the gut, in addition to in vivo read outs of SCFAs produced in response to specific fiber spike-ins, these data suggest that optimizing SCFA production in a given individual through targeted fiber supplementation requires quantitative understanding of their MMP.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Bacteria / genetics
  • Bacteria / isolation & purification
  • Bacteria / metabolism
  • Biological Variation, Individual
  • Dietary Carbohydrates / metabolism
  • Dietary Fiber / metabolism*
  • Fatty Acids, Volatile / biosynthesis*
  • Feces / microbiology
  • Female
  • Fermentation*
  • Follow-Up Studies
  • Gastrointestinal Microbiome / physiology*
  • Humans
  • Intestinal Absorption
  • Inulin / analysis
  • Machine Learning
  • Male
  • Phenotype
  • Polysaccharides / metabolism
  • RNA, Bacterial / genetics
  • RNA, Ribosomal, 16S / genetics
  • Ribotyping
  • Young Adult

Substances

  • Dietary Carbohydrates
  • Dietary Fiber
  • Fatty Acids, Volatile
  • Polysaccharides
  • RNA, Bacterial
  • RNA, Ribosomal, 16S
  • Inulin

Grants and funding

This work was funded by the Center for Microbiome Informatics & Therapeutics and the Rasmussen Family Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.