Microbiomes in light of traits: A phylogenetic perspective
Microbial communities – microbiomes – are intricately linked to human health and critical ecosystem services. Despite their recognized importance, however, we still lack a systematic understanding of what determines microbiome diversity and composition and its implications for system functioning. Although new genetic technologies quickly characterize thousands of microbiome samples at a time, a remaining question is how to interpret this variation.
A focus on microbial traits could help address this challenge. Despite sometimes rampant levels of horizontal gene transfer, recent work indicates that many microbial traits are phylogenetically conserved across the Bacteria and Archaea, as well as microbial eukaryotes like the Fungi. We reviewed literature from environmental and host-associated studies to investigate the phylogenetic conservation of various microbial traits.
The degree of phylogenetic conservation depends on the particular microbial trait, leading to a hierarchical distribution of trait variability across the microbial tree-of-life. Traits related to redox conditions, pH, and salinity tolerance appear to the most deeply conserved, whereas those involved in phosphate uptake, phage resistance, and virulence are only finely conserved. Such patterns allow one to predict how microbial community composition should shift as environmental condition change. For instance, bacterial glycoside hydrolase (GH) genes – responsible for the degradation of carbohydrates – are generally conserved at the genus or species level. This corresponds to the level at which the human gut microbiome shifts with diet. Similarly, GH genes encoding cellulases in decomposing plant litter are also highly correlated to genus-level composition.
A phylogenetic framework of microbial traits holds great promise for advancing the interpretation of the rapidly accumulating amount of microbiome data. Not only does the framework provide a path to compare results across systems and taxa, it can be applied across different levels of genetic resolution, from studies examining strain- or population- level differences to those considering the entire microbial community. Such a flexible framework is sorely needed for microorganisms, where the times scales of evolutionary and ecological processes overlap.