Functional metagenomic screening in microfluidic droplets identifies a β-glucuronidase in an unprecedented sequence neighbourhood

Abstract

The abundance of recorded protein sequence data stands in contrast to the small number of experimentally verified functional annotation. Here we screened a million-membered metagenomic library at ultrahigh throughput in microfluidic droplets for {beta}-glucuronidase activity. We identified SN243, a genuine {beta}-glucuronidase with little homology to previously studied enzymes of this type, as a glycoside hydrolase (GH) 3 family member. This GH family had no recorded evidence of {beta}-glucuronidases at the outset of this study, showing that a functional metagenomic approach can shed light on assignments that are currently unpredictable by bioinformatics. Kinetic analyses of SN243 characterised it as a promiscuous catalyst and structural analysis suggests regions of divergence from homologous GH3 members creating a wide-open active site. With a screening throughput of >107 library members per day, picolitre volume microfluidic droplets enable functional assignments that complement current enzyme database dictionaries and provide bridgeheads for the annotation of unexplored sequence space.