An eco-evolutionary theory of host-associated microbiomes
Araujo, G. D.; Thomas, T.; Webster, N. S.; Montoya, J. M.; Lurgi, M.
Show abstract
Host-associated microbiomes often display host specificity and heritability, yet the evolutionary processes under which such structured communities first emerge are still unclear. In particular, the conditions by which intergenerational (i.e. vertical) transmission of microbes can evolve and generate host-specific microbiomes are still unresolved. Here, we present an eco-evolutionary theory of microbiome assembly under minimal assumptions of microbial dynamics (i.e. neutrally driven by environmental fluctuations) and host control. We consider the adaptive evolution of microbial and host traits, including microbiome size and vertical transmission. We show that environmental fluctuations can generate enough among-host microbial variation to enable host-level selection favouring beneficial microbiome configurations. Vertical transmission can then evolve and, even when weak, allow microbiome specificity to be inherited and amplified across generations despite continuous influx from the external environment. Selection is most effective at intermediate levels of environmental fluctuation and host lifespan, revealing fundamental trade-offs between stochastic assembly, inheritance, and dispersal of microbes. The resulting microbiomes are dense, host-specific, and heritable, yet retain high intraspecific variability and lack strict phylosymbiosis. Simulated patterns of microbial dominance, diversity, and host-microbiome dissimilarity closely match those observed in nature, as evidenced using marine sponge microbiomes. Our results provide a mechanistic theory for the early evolution of host-associated microbiomes, showing that beneficial and species-specific communities can arise through selection and inheritance prior to the evolution of dedicated host-control mechanisms.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.