Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling.

ABSTRACT: The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational prediction

SUBMITTER: Larsen PE 

PROVIDER: S-EPMC4557938 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature