Leveraging phylogenetic signal to unravel microbiome function and assembly rules

Abstract

Clarifying the general rules behind microbial community assembly will foster the development of microbiome-based technological solutions. Here, we study microbial community assembly through a computational analysis of phylogenetic core groups (PCGs): discrete portions of the bacterial phylogeny with high prevalence in the ecosystem under study. We first show that the existence of PCGs was a predominant feature of the varied set of microbial ecosystems studied. Then, we re-analyzed an in vitro experimental dataset using a PCG-based approach, drawing only from its community composition data and from publicly available genomic databases. Using mainly genome scale metabolic models and population dynamics modeling, we obtained ecological insights on metabolic niche structure and population dynamics comparable to those gained after canonical experimentation. Thus, leveraging phylogenetic signal to help unravel microbiome function and assembly rules offers a potential avenue to gain further insight on Earth’s microbial ecosystems.

Keywords

• Community assembly
• Microbiome
• Phylogenetic clustering
• 16S rRNA gene
• Metabolic modeling
• Microbial ecology