bioRxiv (Cold Spring Harbor Laboratory) · 2024 · 15 citations · 37 references
Life SciencesMicrobiologyMedical MicrobiologyMetagenomicsMicrobiome ResearchMetagenomic AnalysisMicrobial Community ProfilingMicrobiome DysbiosisCommunity CompositionCovariate SelectionIntestinal DysbiosisMicrobial Community Composition
Summary Background Enterotypes describe human fecal microbiomes grouped by similarity into clusters of microbial community composition, often associated with disease, medications, diet, and lifestyle. Numbers and determinants of enterotypes have been derived by diverse frameworks and applied to cohorts that often lack diversity or inter-cohort comparability. Results To overcome these limitations, we selected 16,772 fecal metagenomes collected from 38 countries to revisit the enterotypes using state-of-the-art fuzzy clustering and found robust clustering regardless of underlying taxonomy, consistent with previous findings. Quantifying the strength of enterotype classifications enriched the enterotype landscape, also reflecting some continuity of microbial compositions. As the classification strength was associated with the patient’s health status, we established an “Enterotype Dysbiosis Score” (EDS) as a latent covariate for various diseases. Conclusion This global study confirms the enterotypes, reveals a dysbiosis signal within the enterotype landscape, and enables robust classification of metagenomes with an online “Enterotyper” tool, allowing reproducible analysis in future studies. Graphical Abstract
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