Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

ABSTRACT: A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, th

SUBMITTER: Kim M 

PROVIDER: S-EPMC4361189 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature