Metabolic pathway prediction of core microbiome based on enterotype and orotype

Front Cell Infect Microbiol. 2023 Jun 22:13:1173085. doi: 10.3389/fcimb.2023.1173085. eCollection 2023.

Abstract

Introduction: Identification of key microbiome components has been suggested to help address the maintenance of oral and intestinal health in humans. The core microbiome is similar in all individuals, whereas the diverse microbiome varies across individuals, based on their unique lifestyles and phenotypic and genotypic determinants. In this study, we aimed to predict the metabolism of core microorganisms in the gut and oral environment based on enterotyping and orotyping.

Materials and methods: Gut and oral samples were collected from 83 Korean women aged 50 years or older. The extracted DNA was subjected to next-generation sequencing analysis of 16S rRNA hypervariable regions V3-V4.

Results: Gut bacteria were clustered into three enterotypes, while oral bacteria were clustered into three orotypes. Sixty-three of the core microbiome between the gut and oral population were correlated, and different metabolic pathways were predicted for each type. Eubacterium_g11, Actinomyces, Atopobium, and Enterococcus were significantly positively correlated between the gut and oral abundance. The four bacteria were classified as type 3 in orotype and type 2 in enterotype.

Conclusion: Overall, the study suggested that collapsing the human body's multidimensional microbiome into a few categories may help characterize the microbiomes better and address health issues more deeply.

Keywords: Actinomyces; Atopobium; Enterococcus; Eubacterium_g11; core microbiome; gut microbiome; oral microbiome; oral-gut axis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria / genetics
  • Feces / microbiology
  • Female
  • Gastrointestinal Microbiome* / genetics
  • Humans
  • Metabolic Networks and Pathways
  • Microbiota* / genetics
  • RNA, Ribosomal, 16S / genetics

Substances

  • RNA, Ribosomal, 16S

Grants and funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1F1A1063928).