During the past decade, meta-omics approaches have revolutionized microbiology, allowing for a cultivation-free assessment of the composition and functional properties of entire microbial ecosystems. On the one hand, a phylogenetic and functional interpretation of such data relies on accumulated genetic, biochemical, metabolic, and phenotypic characterization of microbial variation. On the other hand, the increasing availability of extensive microbiome data sets and corresponding metadata provides a vast, underused resource for the microbiology field as a whole. To demonstrate the potential for integrating big data into a functional microbiology workflow, we review literature on trimethylamine (TMA), a microbiota-generated metabolite linked to atherosclerosis development. Translating recently elucidated microbial pathways resulting in TMA production into genomic orthologs, we demonstrate how to mine for their presence in public (meta-) genomic databases and link findings to associated metadata. Reviewing pathway abundance in public data sets shows that TMA production potential is associated with symptomatic atherosclerosis and allows identification of currently uncharacterized TMA-producing bacteria.