Mining metagenomic data to gain a new insight into the gut microbial biosynthetic potential in placental mammals

Abstract

ABSTRACT Mammals host a remarkable diversity and abundance of gut microbes. Biosynthetic gene clusters (BGCs) in microbial genomes encode biologically active chemical products and play an important role in microbe–host interactions. Traditionally, the exploration of gut microbial metabolic functions has relied on the pure culture method. However, given the limited amounts of microbes being cultivated, insights into the metabolism of gut microbes in mammals continued to be very limited. In this study, we adopted a computational pipeline for mining the metagenomic data (named taxonomy-guided identification of biosynthetic gene clusters, TaxiBGC) to identify experimentally verified BGCs in 373 metagenomes across 53 mammalian species in an unbiased manner. We demonstrated that polyketides (PKs) and nonribosomal peptides (NRPs) are representative of mammals, and the products derived from them were associated with cell–cell communication and resistance to inflammation. Large carnivores had the highest number of BGCs, followed by large herbivores and small mammals. We also observed that the large mammals had more common BGCs that aid in the biosynthesis of a variety of natural products. However, small mammals not only had fewer BGCs but were also unique to each species. Our results provide novel insights into the mining of metagenomic data sets to identify active BGCs and their products across mammals. IMPORTANCE The gut microbes host numerous biosynthetic gene clusters (BGCs) that biosynthesize natural products and impact the host’s physiology. Historically, our understanding of BGCs in mammalian gut microbes was largely based on studies on cultured isolates; however, only a small fraction of mammal-associated microbes have been investigated. The biochemical diversity of the mammalian gut microbiota is poorly understood. Metagenomic sequencing contains data from a vast number of organisms and provides information on the total gene content of communities. Unfortunately, the existing BGC prediction tools are designed for individual microbial genomes. Recently, a BGC prediction tool called the taxonomy-guided identification of biosynthetic gene clusters (TaxiBGC) that directly mine the metagenome was developed. To gain new insights into the microbial metabolism, we used TaxiBGC to predict BGCs from 373 metagenomes across 53 mammalian species representing seven orders. Our findings elucidate the functional activities of complex microbial communities in the gut.