Microbiome spectra serve as critical clues to elucidate the evolutionary biology pathways, potential pathologies, and even behavioral patterns of the host organisms. Furthermore, exotic sources of microbiota represent an unexplored niche to discover microbial secondary metabolites. However, establishing the bacterial functionality is complicated by an intricate web of interactions inside the microbiome. Here we apply an ultrahigh-throughput (uHT) microfluidic droplet platform for activity profiling of the entire oral microbial community of the Siberian bear to isolate Bacillus strains demonstrating antimicrobial activity against Staphylococcus aureus Genome mining allowed us to identify antibiotic amicoumacin A (Ami) as responsible for inhibiting the growth of S. aureus Proteomics and metabolomics revealed a unique mechanism of Bacillus self-resistance to Ami, based on a subtle equilibrium of its deactivation and activation by kinase AmiN and phosphatase AmiO, respectively. We developed uHT quantitative single-cell analysis to estimate antibiotic efficacy toward different microbiomes and used it to determine the activity spectra of Ami toward human and Siberian bear microbiota. Thus, uHT microfluidic droplet platform activity profiling is a powerful tool for discovering antibiotics and quantifying external influences on a microbiome.
Keywords: antibiotic resistance; deep functional profiling; microbiome; microfluidics; single-cell cultivation.
Copyright © 2018 the Author(s). Published by PNAS.