Gene clusters once hidden in the human microbiome, whose products resemble clinically used drugs, are now more discoverable, thanks to a new bioinformatics approach. Dubbed MetaBGC, it may be useful for "bioprospecting" human microbiome samples for genes whose protein products have features like antimicrobial properties. The composition of the human microbiome has been correlated with several health-promoting as well as disease states, but the mechanisms and molecules governing the functions of the microbiota remain largely unexplored. Research has shown the microbiome can produce an array of small molecule products, though systematic approaches for discovering and characterizing these are lacking. Here, Yuki Sugimoto and colleagues developed a computational algorithm, MetaBGC, designed to identify biologically active small molecules encoded directly in human microbiome-derived sequencing data. They tested MetaBGC by running it on human microbiome samples, searching for a class of small molecule that has never been reported from the human microbiome, a TII-PKS biosynthetic gene cluster (BCG). The researchers uncovered several novel TII-PKS BGCs in three body sites (mouth, gut, and skin), indicating that this class of molecules is indeed encoded in human-derived metagenomes despite not having been reported from common isolates of the human microbiome. Several of the novel TII-PKS BGCs they found have antimicrobial activity against neighboring microbes, the authors report, as well as anti-cancer effects. Further studies of their approach, all showing its efficacy, involved human microbiome samples from subjects from the USA, Denmark, Spain, Fiji and China. The approach offers a generalizable platform.
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Journal
Science