Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

The current paradigm, widely incorporated in soil biogeochemical models, is that microbial methanogenesis can only occur in anoxic habitats. In contrast, here we show clear geochemical and biological evidence for methane production in well-oxygenated soils of a freshwater wetland. A comparison of oxic to anoxic soils reveal up to ten times greater methane production and nine times more methanogenesis activity in oxygenated soils. Metagenomic and metatranscriptomic sequencing recover the first near-complete genomes for a novel methanogen species, and show acetoclastic production from this organism was the dominant methanogenesis pathway in oxygenated soils. This organism, Candidatus Methanothrix paradoxum, is prevalent across methane emitting ecosystems, suggesting a global significance. Moreover, in this wetland, we estimate that up to 80% of methane fluxes could be attributed to methanogenesis in oxygenated soils. Together, our findings challenge a widely held assumption about methanogenesis, with significant ramifications for global methane estimates and Earth system modeling.

ABSTRACTMicrobial and viral communities transform the chemistry of Earth’s ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles, and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

Here we used soil metagenomics and metatranscriptomics to uncover novel members within the genus Methylobacter. We denote these closely related genomes as members of the lineage OWC Methylobacter. Despite the incredibly high microbial diversity in soils, here we present findings that unexpectedly showed that methane cycling was primarily mediated by a single genus for both methane production (“Candidatus Methanothrix paradoxum”) and methane consumption (OWC Methylobacter). Metatranscriptomic analyses revealed that decreased methanotrophic activity rather than increased methanogenic activity possibly contributed to the greater methane emissions that we had previously observed in summer months, findings important for biogeochemical methane models. Although members of this Methylococcales order have been cultivated for decades, multi-omic approaches continue to illuminate the methanotroph phylogenetic and metabolic diversity harbored in terrestrial and marine ecosystems.

Inland waters are increasingly recognized as critical sites of methane emissions to the atmosphere, but the biogeochemical reactions driving such fluxes are less well understood. The Prairie Pothole Region (PPR) of North America is one of the largest wetland complexes in the world, containing millions of small, shallow wetlands. The sediment pore waters of PPR wetlands contain some of the highest concentrations of dissolved organic carbon (DOC) and sulfur species ever recorded in terrestrial aquatic environments. Using a suite of geochemical and microbiological analyses, we measured the impact of sedimentary carbon and sulfur transformations in these wetlands on methane fluxes to the atmosphere. This research represents the first study of coupled geochemistry and microbiology within the PPR and demonstrates how the conversion of abundant labile DOC pools into methane results in some of the highest fluxes of this greenhouse gas to the atmosphere ever reported. Abundant DOC and sulfate additionally supported some of the highest sulfate reduction rates ever measured in terrestrial aquatic environments, which we infer to account for a large fraction of carbon mineralization in this system. Methane accumulations in zones of active sulfate reduction may be due to either the transport of free methane gas from deeper locations or the co-occurrence of methanogenesis and sulfate reduction. If both respiratory processes are concurrent, any competitive inhibition of methanogenesis by sulfate-reducing bacteria may be lessened by the presence of large labile DOC pools that yield noncompetitive substrates such as methanol. Our results reveal some of the underlying mechanisms that make PPR wetlands biogeochemical hotspots, which ultimately leads to their critical, but poorly recognized role in regional greenhouse gas emissions.