Despite the current wealth of sequencing data, one-third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome-scale metabolic models with these new sequence-function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction.

Using metagenomic 'parts lists' to infer global patterns on microbial ecology remains a significant challenge. To deduce important ecological indicators such as environmental adaptation, molecular trait dispersal, diversity variation and primary production from the gene pool of an ecosystem, we integrated 25 ocean metagenomes with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the biomolecular repertoire of each sample and the main limiting factor on functional trait dispersal (absence of biogeographic provincialism). Molecular functional richness and diversity show a distinct latitudinal gradient peaking at 20°N and correlate with primary production. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes is an important quantitative readout for molecular trait-based biogeography and ecology.

To investigate the extent of genetic stratification in structured microbial communities, we compared the metagenomes of 10 successive layers of a phylogenetically complex hypersaline mat from Guerrero Negro, Mexico. We found pronounced millimeter-scale genetic gradients that were consistent with the physicochemical profile of the mat. Despite these gradients, all layers displayed near-identical and acid-shifted isoelectric point profiles due to a molecular convergence of amino-acid usage, indicating that hypersalinity enforces an overriding selective pressure on the mat community.