A prominent glycyl radical enzyme in human gut microbiomes metabolizes trans-4-hydroxy-l-proline.

The human microbiome encodes vast numbers of uncharacterized enzymes, limiting our functional understanding of this community and its effects on host health and disease. By incorporating information about enzymatic chemistry into quantitative metagenomics, we determined the abundance and distribution of individual members of the glycyl radical enzyme superfamily among the microbiomes of healthy humans. We identified many uncharacterized family members, including a universally distributed enzyme that enables commensal gut microbes and human pathogens to dehydrate trans-4-hydroxy-l-proline, the product of the most abundant human posttranslational modification. This "chemically guided functional profiling" workflow can therefore use ecological context to facilitate the discovery of enzymes in microbial communities.

Assessing the functional structure of genomic data.

MOTIVATION: The availability of genome-scale data has enabled an abundance of novel analysis techniques for investigating a variety of systems-level biological relationships. As thousands of such datasets become available, they provide an opportunity to study high-level associations between cellular pathways and processes. This also allows the exploration of shared functional enrichments between diverse biological datasets, and it serves to direct experimenters to areas of low data coverage or with high probability of new discoveries. RESULTS: We analyze the functional structure of Saccharomyces cerevisiae datasets from over 950 publications in the context of over 140 biological processes. This includes a coverage analysis of biological processes given current high-throughput data, a data-driven map of associations between processes, and a measure of similar functional activity between genome-scale datasets. This uncovers subtle gene expression similarities in three otherwise disparate microarray datasets due to a shared strain background. We also provide several means of predicting areas of yeast biology likely to benefit from additional high-throughput experimental screens. AVAILABILITY: Predictions are provided in supplementary tables; software and additional data are available from the authors by request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.