Selection and enrichment of microbial species with an increased lignocellulolytic phenotype from a native soil microbiome by activity-based probing

Abstract

Multi-omic analyses can provide information on the potential for activity within a microbial community but often lack specificity to link functions to cell, primarily offer potential for function or rely on annotated databases. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce a pipeline of coupling activity-based probing with fluorescence-activated cell sorting, culturing, and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied our approach to a soil microbiome using two activity-based probes to enrich for communities with elevated activity for lignocellulose-degradation phenotypes as determined by four fluorogenic kinetic assays. Our approach efficiently separated and identified microbial members with heightened activity for glycosyl hydrolases, and by expanding this workflow to various probes for other function, this process can be applied to unique phenotype targets of interest.

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

“…Only recently, the use of ABPP in biocatalyst discovery for industrial applications, for example for elucidating lignocellulose-degrading enzymes, has emerged [ 39 – 41 ]. In addition, first reports on the use of ABPP or related approaches for studying microbial communities and isolating functionally active subpopulations, with a focus on host-associated microbial communities, have been made [ 42 – 44 ]. Among these, few studies on the gut microbiome have implemented a combination of ABPP with metagenomics to facilitate the identification of enzymes related to chronic inflammation, drug toxicity, or dietary fiber metabolism in the gastrointestinal tract by employing a metaproteome database that was either constructed from publicly available genomes or self-constructed based on metagenome sequencing [ 45 – 47 ].…”