Identifying microbiota community patterns important for plant protection using synthetic communities and machine learning.

ABSTRACT: Plant-associated microbiomes contribute to important ecosystem functions such as host resistance to biotic and abiotic stresses. The factors that determine such community outcomes are inherently difficult to identify under complex environmental conditions. In this study, we present an experimental and analytical approach to explore microbiota properties relevant for a microbiota-conferred host phenotype, here plant protection, in a reductionist system. We screened 136 randomly assembled synthetic communities (SynComs) of five bacterial strains each, followed by classification and regression analyses as well as empirical validation to test potential explanatory factors of community structure and composition, including evenness, total commensal colonization, phylogenetic diversity, and strai

SUBMITTER: Emmenegger B 

PROVIDER: S-EPMC10693592 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature