Functional metaproteomics for enzyme discovery

Discovery of microbial biocatalysts traditionally relied on activity screening of isolated bacterial strains. However, since most microorganisms cannot be cultivated in the lab, such an approach leaves the majority of the microbial enzyme diversity untapped. Metagenomic approaches, in which the DNA from a microbial community is directly isolated and then used either for the creation of an expression library or for sequencing and metagenome annotation have alleviated this shortcoming to an extent, but have their own limitations: the generation of large expression libraries is time-consuming and their screening is costly, while metagenome annotation can infer biocatalytic function only from prior knowledge. We have thus developed a functional metaproteomic approach, which combines the immediacy of traditional activity screening with the comprehensiveness of a meta-omics approach. Briefly, the whole metaproteome of an environmental sample is separated on a 2-D gel, biocatalytically active proteins are visualized in-gel through zymography, and those candidate biocatalysts are then identified through mass spectrometry, searching against a metagenome-derived database obtained from the very same environmental sample. Here we explain the process in detail, with a focus on esterases, and give guidelines on how to develop a functional metaproteomic workflow for enzyme discovery.