Exploration of bacterial community classes in major human habitats
1 The Genome Institute, Washington University, St Louis, MO 63108, USA
2 Medical School of Indiana University at Indianapolis, Indianapolis, IN 46202, USA
3 Washington University School of Medicine, Biostatistics in Medicine, St Louis, MO 63110, USA
4 Department of Pediatrics, Washington University School of Medicine, St Louis, MO 63110, USA
5 Current address: The Jackson Laboratory for Genomic Medicine, c/o University of Connecticut Health Center, 263 Farmington Avenue. Administrative Services Building, Call Box 901, Farmington, CT 06030, USA
Genome Biology 2014, 15:R66 doi:10.1186/gb-2014-15-5-r66Published: 7 May 2014
Determining bacterial abundance variation is the first step in understanding bacterial similarity between individuals. Categorization of bacterial communities into groups or community classes is the subsequent step in describing microbial distribution based on abundance patterns. Here, we present an analysis of the groupings of bacterial communities in stool, nasal, skin, vaginal and oral habitats in a healthy cohort of 236 subjects from the Human Microbiome Project.
We identify distinct community group patterns in the anterior nares, four skin sites, and vagina at the genus level. We also confirm three enterotypes previously identified in stools. We identify two clusters with low silhouette values in most oral sites, in which bacterial communities are more homogeneous. Subjects sharing a community class in one habitat do not necessarily share a community class in another, except in the three vaginal sites and the symmetric habitats of the left and right retroauricular creases. Demographic factors, including gender, age, and ethnicity, significantly influence community composition in several habitats. Community classes in the vagina, retroauricular crease and stool are stable over approximately 200 days.
The community composition, association of demographic factors with community classes, and demonstration of community stability deepen our understanding of the variability and dynamics of human microbiomes. This also has significant implications for experimental designs that seek microbial correlations with clinical phenotypes.