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Proc Natl Acad Sci U S A. 2018 Sep 18;115(38):9551-9556. doi: 10.1073/pnas.1811250115. Epub 2018 Sep 4.

Ultrahigh-throughput functional profiling of microbiota communities.

Author information

1
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia.
2
National Research University Higher School of Economics, 101000 Moscow, Russia.
3
Federal Research and Clinical Centre of Physical-Chemical Medicine, Federal Medical and Biological Agency, 119435 Moscow, Russia.
4
Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia.
5
Skolkovo Institute of Science and Technology, 143026 Skolkovo, Russia.
6
Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
7
Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia.
8
Skolkovo Institute of Science and Technology, 143026 Skolkovo, Russia; severik@waksman.rutgers.edu gabibov@ibch.ru sidney.altman@yale.edu.
9
Waksman Institute for Microbiology, Rutgers, The State University of New Jersey, Piscataway, NJ 08901.
10
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia; severik@waksman.rutgers.edu gabibov@ibch.ru sidney.altman@yale.edu.
11
Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520; severik@waksman.rutgers.edu gabibov@ibch.ru sidney.altman@yale.edu.
12
School of Life Sciences, Arizona State University, Tempe, AZ 85287.

Abstract

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

PMID:
30181282
DOI:
10.1073/pnas.1811250115
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Conflict of interest statement

The authors declare no conflict of interest.

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