Environmental activity-based protein profiling for function-driven enzyme discovery from natural communities.

ABSTRACT

BACKGROUND: Microbial communities are important drivers of global biogeochemical cycles, xenobiotic detoxification, as well as organic matter decomposition. Their major metabolic role in ecosystem functioning is ensured by a unique set of enzymes, providing a tremendous yet mostly hidden enzymatic potential. Exploring this enzymatic repertoire is therefore not only relevant for a better understanding of how microorganisms function in their natural environment, and thus for ecological research, but further turns microbial communities, in particular from extreme habitats, into a valuable resource for the discovery of novel enzymes with potential applications in biotechnology. Different strategies for their uncovering such as bioprospecting, which relies mainly on metagenomic approaches in combination with sequence-based bioinformatic analyses, have emerged; yet accurate function prediction of their proteomes and deciphering the in vivo activity of an enzyme remains challenging. RESULTS: Here, we present environmental activity-based protein profiling (eABPP), a multi-omics approach that extends genome-resolved metagenomics with mass spectrometry-based ABPP. This combination allows direct profiling of environmental community samples in their native habitat and the identification of active enzymes based on their function, even without sequence or structural homologies to annotated enzyme families. eABPP thus bridges the gap between environmental genomics, correct function annotation, and in vivo enzyme activity. As a showcase, we report the successful identification of active thermostable serine hydrolases from eABPP of natural microbial communities from two independent hot springs in Kamchatka, Russia. CONCLUSIONS: By reporting enzyme activities within an ecosystem in their native state, we anticipate that eABPP will not only advance current methodological approaches to sequence homology-guided enzyme discovery from environmental ecosystems for subsequent biocatalyst development but also contributes to the ecological investigation of microbial community interactions by dissecting their underlying molecular mechanisms.