Predicted Relative Metabolomic Turnover - Predicting Changes in the Environmental Metabolome from the Metagenome

Metagenomics, the sequencing and analysis of genomic DNA extracted directly from an environment, can provide insight into taxonomic and functional diversity, but there are few tools for directly comparing metabolomes predicted from metagenomic data sets. We present a new method, Predicted Relative Metabolomic Turnover (PRMT), for comparing the predicted environmental metabolomes encoded in separate metagenomes and identifying those compounds predicted to be differentially metabolized. The PRMT method was validated using three separate sets of ocean metagenomic sequence studies, totaling 15 metagenomic samples, over 4.5 million sequence fragments and over 840 million base pairs. These data sets enable the construction of models representative of the environmental metabolome of the English Channel. Not only did 88% of the predicted metabolic Predicted Metabolic Relative Turnover shows excellent correlation with observed oceanographic parameters, but PRMT derived parameters are shown to generate potentially constructive and testable biological hypotheses that could form the basis for future biological