A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets
Year: 2013
Type: review
Abstract: Recent analyses of human-associated bacterial diversity have categorized individuals into 'enterotypes' or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes.
Source: PLoS Computational Biology
Language: English
Topic: Gut microbiota and health
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,043
Funders: National Science Foundation, David and Lucile Packard Foundation, Howard Hughes Medical Institute, Arnold and Mabel Beckman Foundation, Hartwell Foundation, Danone, Crohn's and Colitis Foundation, National Energy Research Scientific Computing Center, National Institutes of Health, National Human Genome Research Institute
Awards: A Quality Assurance, Coordination and Analysis Center for HMP, Functional activity and inter-organismal interactions in the human microbiome, G4001477574, New Tools for Understanding the Composition and Dynamics of Microbial Communities, G4771863138, CAREER: Scalable Computational Models for Multicellular Systems Biology, G8091516379, G8112690214, G8873824821
OpenAlex ID: W2118629634
