Pyrosequencing-based analysis of the mucosal microbiota in healthy individuals reveals ubiquitous bacterial groups and micro-heterogeneity

PLoS One. 2011;6(9):e25042. doi: 10.1371/journal.pone.0025042. Epub 2011 Sep 22.

Abstract

This study used 16S rRNA-based pyrosequencing to examine the microbial community that is closely associated with the colonic mucosa of five healthy individuals. Spatial heterogeneity in microbiota was measured at right colon, left colon and rectum, and between biopsy duplicates spaced 1 cm apart. The data demonstrate that mucosal-associated microbiota is comprised of Firmicutes (50.9% ± 21.3%), Bacteroidetes (40.2% ± 23.8%) and Proteobacteria (8.6%± 4.7%), and that interindividual differences were apparent. Among the genera, Bacteroides, Leuconostoc and Weissella were present at high abundance (4.6% to 41.2%) in more than 90% of the studied biopsy samples. Lactococcus, Streptococcus, Acidovorax, Acinetobacter, Blautia, Faecalibacterium, Veillonella, and several unclassified bacterial groups were also ubiquitously present at an abundance <7.0% of total microbial community. With the exception of one individual, the mucosal-associated microbiota was relatively homogeneous along the colon (average 61% Bray-Curtis similarity). However, micro-heterogeneity was observed in biopsy duplicates within defined colonic sites for three of the individuals. A weak but significant Mantel correlation of 0.13 was observed between the abundance of acidomucins and mucosal-associated microbiota (P-value = 0.04), indicating that the localized biochemical differences may contribute in part to the micro-heterogeneity. This study provided a detailed insight to the baseline mucosal microbiota along the colon, and revealed the existence of micro-heterogeneity within defined colonic sites for certain individuals.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Algorithms
  • Biopsy
  • Female
  • Gastrointestinal Tract / microbiology
  • Genetic Techniques
  • Genome, Bacterial*
  • Humans
  • Male
  • Metagenome / physiology*
  • Microbiological Techniques
  • Middle Aged
  • Models, Statistical
  • Mucins / metabolism
  • RNA, Ribosomal, 16S / genetics*
  • RNA, Ribosomal, 16S / metabolism
  • Regression Analysis
  • Reproducibility of Results
  • Sequence Analysis, DNA / methods*

Substances

  • Mucins
  • RNA, Ribosomal, 16S