Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model.

ABSTRACT: Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherent

SUBMITTER: Marschmann GL 

PROVIDER: S-EPMC10847045 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature