A metagenomic strategy for harnessing the chemical repertoire of the human microbiome

• Published in: Science (American Association for the Advancement of Science) Vol. 366; no. 6471; p. 1332
• Main Authors: Sugimoto, Yuki, Camacho, Francine R., Wang, Shuo, Chankhamjon, Pranatchareeya, Odabas, Arman, Biswas, Abhishek, Jeffrey, Philip D., Donia, Mohamed S.
• Format: Journal Article
• Language: English
• Published: United States American Association for the Advancement of Science 13.12.2019; The American Association for the Advancement of Science
• Subjects: Algorithms; Antibiotics; Antineoplastic drugs; Bacteria; Chemical potential; Datasets; Genes; Gram-positive bacteria; Host Microbial Interactions - genetics; Human Body; Human populations; Humans; Intestinal microflora; Mathematical models; Mathematics; Metagenome; Metagenomics - methods; Microbiomes; Microbiota - genetics; Multigene Family; Narcotics; Niches; Polyketides - chemistry; Polyketides - metabolism; RESEARCH ARTICLE SUMMARY; Skin; Synthetic biology; United States > US
• ISSN: 0036-8075; 1095-9203; 1095-9203
• DOI: 10.1126/science.aax9176

The microbiome is an important source of natural products that can profoundly influence health and disease in the host. Sugimoto et al. constructed a modular, probabilistic strategy called MetaBGC to uncover biosynthetic gene clusters (BGCs) in human microbiome samples (see the Perspective by Henke and Clardy). The authors found geographic and strain-specific distributions of BGCs. By zeroing in on two type II aromatic polyketides, the native organisms were identified, the BGCs were reconstructed in Streptomyces , and the products were characterized. When expressed in Bacillus subtilis , the products resembled currently used anticancer drugs and antibiotics. These polyketides were not cytotoxic but had inhibitory activity against oral Gram-positive bacteria, which may reflect the niche and ecology of the originating organisms. Science , this issue p. eaax9176 ; see also p. 1309 A general strategy quickly profiles metagenomic datasets from large clinical cohorts, prioritizing candidate biosynthetic gene clusters. Extensive progress has been made in determining the effects of the microbiome on human physiology and disease, but the underlying molecules and mechanisms governing these effects remain largely unexplored. Here, we combine a new computational algorithm with synthetic biology to access biologically active small molecules encoded directly in human microbiome–derived metagenomic sequencing data. We discover that members of a clinically used class of molecules are widely encoded in the human microbiome and that they exert potent antibacterial activities against neighboring microbes, implying a possible role in niche competition and host defense. Our approach paves the way toward a systematic unveiling of the chemical repertoire encoded by the human microbiome and provides a generalizable platform for discovering molecular mediators of microbiome-host and microbiome-microbiome interactions.