A Metabolome- and Metagenome-Wide Association Network Reveals Microbial Natural Products and Microbial Biotransformation Products from the Human Microbiota

Abstract

The human microbiome consists of thousands of different microbial species, and tens of thousands of bioactive small molecules are associated with them. These associated molecules include the biosynthetic products of microbiota and the products of microbial transformation of host molecules, dietary components, and pharmaceuticals. The existing methods for characterization of these small molecules are currently time consuming and expensive, and they are limited to the cultivable bacteria. Here, we propose a method for detecting microbiota-associated small molecules based on the patterns of cooccurrence of molecular and microbial features across multiple microbiomes. We further map each molecule to the clade in a phylogenetic tree that is responsible for its production/transformation. We applied our proposed method to the tandem mass spectrometry and metagenomics data sets collected by the American Gut Project and to microbiome isolates from cystic fibrosis patients and discovered the genes in the human microbiome responsible for the production of corynomycolenic acid, which serves as a ligand for human T cells and induces a specific immune response against infection. Moreover, our method correctly associated pseudomonas quinolone signals, tyrvalin, and phevalin with their known biosynthetic gene clusters. IMPORTANCE Experimental advances have enabled the acquisition of tandem mass spectrometry and metagenomics sequencing data from tens of thousands of environmental/host-oriented microbial communities. Each of these communities contains hundreds of microbial features (corresponding to microbial species) and thousands of molecular features (corresponding to microbial natural products). However, with the current technology, it is very difficult to identify the microbial species responsible for the production/biotransformation of each molecular feature. Here, we develop association networks, a new approach for identifying the microbial producer/biotransformer of natural products through cooccurrence analysis of metagenomics and mass spectrometry data collected on multiple microbiomes.

MolDiscovery: Learning Mass Spectrometry Fragmentation of Small Molecules

“…In addition, parent fragments with high ranks are more likely to produce high-rank children fragments, while fragments with low ranks are similar to random noise. For example, for fragments produced by the breakage of OC bond ( Figure 2B), if their parents have high ranks (1, 2 or 3), they are likely to be higher rank than those with lower-rank parents (6,7). Moreover, molDiscovery automatically learns to discard fragments with low rank parents which are not informative for predicting mass spectrometry fragmentations.…”

Linking genomics and metabolomics to chart specialized metabolic diversity

“…Similarly, Cao et al developed a method for detecting microbiota-associated small molecules based on the patterns of co-occurrence of molecular and microbial features across multiple microbiomes, and further mapping each molecule to the phylogenetic clade responsible for its production/ transformation. 53 These approaches aid in linking bacterial taxa or gene clusters to metabolite products using correlation-based or neural networking (machine learning) methods. Ultimately, the success of linking genome and metabolome mining workflows for NP discovery will depend on platform and infrastructure development.…”

The Microbiome in Cystic Fibrosis Pulmonary Disease

“…In microbial ecology, the term "microbiome" also refers to the entire habitat: microorganisms, their genomes, and microscopic environmental conditions (micro-biome) [16,17]. Complete microbiome study further includes intracellular mechanisms and interactions between microorganisms or between microorganisms and their host and environment; this is the aim of complementary approaches such as transcriptomics or metabolomics [18,19]. Disease-associated microbiome alterations are often referred to as a "dysbiosis", a term that is widely used in the microbiome field but remains vaguely defined and is often misused.…”