Multi-omics profiling of Earth’s biomes reveals patterns of diversity and co-occurrence in microbial and metabolite composition across environments

Abstract

Microbes produce an array of secondary metabolites that perform diverse functions from communication to defense. These metabolites have been used to benefit human health and sustainability. In their analysis of the Genomes from Earth's Microbiomes (GEM) catalog, Nayfach and co-authors observed that, whereas genes coding for certain classes of secondary metabolites are limited or enriched in certain microbial taxa, "specific chemistry is not limited or amplified by the environment, and that most classes of secondary metabolites can be found nearly anywhere". Although metagenome mining is a powerful way to annotate biosynthetic gene clusters (BCGs), chemical evidence is required to confirm the presence of metabolites and comprehensively address this fundamental hypothesis, as metagenomic data only identify metabolic potential. To describe the Earth's metabolome, we use an integrated omics approach: the direct survey of metabolites associated with microbial communities spanning diverse environments using untargeted metabolomics coupled with metagenome analysis. We show, in contrast to Nayfach and co-authors, that the presence of certain classes of secondary metabolites can be limited or amplified by the environment. Importantly, our data indicate that considering the relative abundances of secondary metabolites (i.e., rather than only presence/absence) strengthens differences in metabolite profiles across environments, and that their richness and composition in any given sample do not directly reflect those of co-occurring microbial communities, but rather vary with the environment.

Compositionally Aware Phylogenetic Beta-Diversity Measures Better Resolve Microbiomes Associated with Phenotype

“…To benchmark the impact of phylogenetic weighting for RPCA, we created data-driven simulations based on microbiome samples from the Earth Microbiome Project 500 (EMP500). We simulated a shotgun metagenomics data set based on animal, saline, and nonsaline environments ( 16 ) ( Fig. S1 ) (see Materials and Methods for details).…”

“…We utilized a previously published procedure introduced in the original RPCA and CTF manuscripts ( 11 , 12 ). The EMP500 data set was chosen due to the large range in sequencing depths, environments sampled, and distinct three clusters (animal, saline, and nonsaline environments) ( 16 ). The software used to generate the simulations is available at https://github.com/gibsramen/BIRDMAn_Jr .…”

Conceptual strategies for characterizing interactions in microbial communities

“…With the exception of highly sterilized or extreme environments, real-world microbial communities contain a large number of constituents that may be taxonomically and chemically diverse ( Thompson et al., 2017 ; Nayfach et al., 2021 ; Shaffer et al., 2021 ). These complex communities are shaped not only by extrinsic factors but by constraints imposed and opportunities provided by the microbial constituents themselves ( Anantharaman et al., 2016 ; Sung et al., 2017 ; Hug and Co, 2018 ; see review by Weisskopf et al., 2021 ).…”

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

“…Prototypes of the OGU method have already been used in multiple microbiome studies and have obtained biologically relevant results (e.g., see references 24 – 27 ). In this article, we introduce the principles and practices of the OGU method, demonstrate its efficacy in two real-world microbiome data sets, compare it with state-of-the-art metagenome analysis approaches and the alternative data type (i.e., 16S rRNA gene amplicons), and systematically evaluate its performance in various conditions.…”