Journal
SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41598-021-82449-0
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The study analyzes the nature of bacterial associations at the species level in healthy human gut microbiomes, identifying prevalent signature bacterial species that can accurately distinguish between populations. The bacterial association networks reveal conserved associations across populations and a dominance of positive associations over negative associations. Functional analysis suggests that taxonomic variation across human populations does not lead to substantial functional or structural differences.
In a microbial community, associations between constituent members play an important role in determining the overall structure and function of the community. The human gut microbiome is believed to play an integral role in host health and disease. To understand the nature of bacterial associations at the species level in healthy human gut microbiomes, we analyzed previously published collections of whole-genome shotgun sequence data, totaling over 1.6 Tbp, generated from 606 fecal samples obtained from four different healthy human populations. Using a Random Forest Classifier, we identified 202 signature bacterial species that were prevalent in these populations and whose relative abundances could be used to accurately distinguish between the populations. Bacterial association networks were constructed with these signature species using an approach based on the graphical lasso. Network analysis revealed conserved bacterial associations across populations and a dominance of positive associations over negative associations, with this dominance being driven by associations between species that are closely related either taxonomically or functionally. Bacterial species that form network modules, and species that constitute hubs and bottlenecks, were also identified. Functional analysis using protein families suggests that much of the taxonomic variation across human populations does not foment substantial functional or structural differences.
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