Decoding emergent properties of microbial community functions through subcommunity observations and interpretable machine learning.

ABSTRACT: The functions of microbial communities, including substrate conversion and pathogen suppression, arise not as a simple sum of individual species' capabilities but through complex interspecies interactions. Understanding how such functions arise from individual species and their interactions remains a major challenge, limiting efforts to rationally understand microbial roles in both natural and engineered ecosystems. Because current holistic (meta-omics) and reductionist (isolation- or single-cell-based) approaches struggle to capture these emergent microbial community functions, this study explores an intermediate strategy: analyzing simple subcommunity combinations to enable a bottom-up understanding of community-level functions. To examine the validity of this approach, we used a nine-me

SUBMITTER: Ishizawa H 

PROVIDER: S-EPMC12599306 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature