Multi-domain enzymes are cellular machines that orchestrate two or more catalytic activities to carry out metabolic transformations with increased control and speed. Here, we report the development of a new genome mining approach for the targeted discovery of new metabolic pathways based on the cooccurrence of enzyme domains (CO-ED) in a single protein. CO-ED was designed to identify unannotated multifunction proteins for accelerated functional characterization and discovery based on the premise that linked enzyme domains have evolved to function collaboratively. Guided by CO-ED, we targeted an unannotated predicted ThiF-nitroreductase di-domain enzyme found in more than 50 proteobacteria. Through heterologous expression and biochemical reconstitution of this enzyme, we discovered a series of new natural products containing the rare oxazolone heterocycle, and identified the first reported oxazolone synthetase in biology. This proof-of-principle experiment validates CO-ED-guided genome mining as a new method with potential broad utility for both the discovery of novel enzymatic transformations and the functional gene annotation of multi-domain enzymes.
SignificanceBillions of years of evolution has provided immense genetic -and hence, biochemical -diversity, much of which is still un-annotated. Genome mining seeks to explore this "metabolic dark matter" for new pharmaceuticals, biocatalysts and biochemical insight. Historically, these efforts have been guided by sequence homology to known biosynthetic genes, which often leads to re-discovery of known enzymatic transformations. Here, in contrast, we prioritize enzymes harboring multiple catalytic domains in combinations that have not been investigated before. Our approach, "CO-ED", led to the discovery of new natural products and the identification of an enzyme capable of catalyzing the formation of an oxazolone heterocycle, a versatile chemical feedstock. CO-ED has the potential to guide the functional characterization of thousands of unannotated multi-domain enzymes.