Background

Microorganisms drive high rates of methanogenesis and carbon mineralization in wetland ecosystems. These signals are especially pronounced in the Prairie Pothole Region of North America, the tenth largest wetland ecosystem in the world. Sulfate reduction rates up to 22 μmol cm^-3 day^-1 have been measured in these wetland sediments, as well as methane fluxes up to 160 mg m^-2 h^-1-some of the highest emissions ever measured in North American wetlands. While pore waters from PPR wetlands are characterized by high concentrations of sulfur species and dissolved organic carbon, the constraints on microbial activity are poorly understood. Here, we utilized metagenomics to investigate candidate sulfate reducers and methanogens in this ecosystem and identify metabolic and viral controls on microbial activity.

Results

We recovered 162 dsrA and 206 dsrD sequences from 18 sediment metagenomes and reconstructed 24 candidate sulfate reducer genomes assigned to seven phyla. These genomes encoded the potential for utilizing a wide variety of electron donors, such as methanol and other alcohols, methylamines, and glycine betaine. We also identified 37 mcrA sequences spanning five orders and recovered two putative methanogen genomes representing the most abundant taxa-Methanosaeta and Methanoregulaceae. However, given the abundance of Methanofollis-affiliated mcrA sequences, the detection of F420-dependent alcohol dehydrogenases, and millimolar concentrations of ethanol and 2-propanol in sediment pore fluids, we hypothesize that these alcohols may drive a significant fraction of methanogenesis in this ecosystem. Finally, extensive viral novelty was detected, with approximately 80% of viral populations being unclassified at any known taxonomic levels and absent from publicly available databases. Many of these viral populations were predicted to target dominant sulfate reducers and methanogens.

Conclusions

Our results indicate that diversity is likely key to extremely high rates of methanogenesis and sulfate reduction observed in these wetlands. The inferred genomic diversity and metabolic versatility could result from dynamic environmental conditions, viral infections, and niche differentiation in the heterogeneous sediment matrix. These processes likely play an important role in modulating carbon and sulfur cycling in this ecosystem.

Phosphite is the most energetically favorable chemotrophic electron donor known, with a half-cell potential (E^o') of -650 mV for the PO₄^3-/PO₃^3- couple. Since the discovery of microbial dissimilatory phosphite oxidation (DPO) in 2000, the environmental distribution, evolution, and diversity of DPO microorganisms (DPOMs) have remained enigmatic, as only two species have been identified. Here, metagenomic sequencing of phosphite-enriched microbial communities enabled the genome reconstruction and metabolic characterization of 21 additional DPOMs. These DPOMs spanned six classes of bacteria, including the Negativicutes, Desulfotomaculia, Synergistia, Syntrophia, Desulfobacteria, and Desulfomonilia_A Comparing the DPO genes from the genomes of enriched organisms with over 17,000 publicly available metagenomes revealed the global existence of this metabolism in diverse anoxic environments, including wastewaters, sediments, and subsurface aquifers. Despite their newfound environmental and taxonomic diversity, metagenomic analyses suggested that the typical DPOM is a chemolithoautotroph that occupies low-oxygen environments and specializes in phosphite oxidation coupled to CO₂ reduction. Phylogenetic analyses indicated that the DPO genes form a highly conserved cluster that likely has ancient origins predating the split of monoderm and diderm bacteria. By coupling microbial cultivation strategies with metagenomics, these studies highlighted the unsampled metabolic versatility latent in microbial communities. We have uncovered the unexpected prevalence, diversity, biochemical specialization, and ancient origins of a unique metabolism central to the redox cycling of phosphorus, a primary nutrient on Earth.

Microorganisms play vital roles in modulating organic matter decomposition and nutrient cycling in soil ecosystems. The enzyme latch paradigm posits microbial degradation of polyphenols is hindered in anoxic peat leading to polyphenol accumulation, and consequently diminished microbial activity. This model assumes that polyphenols are microbially unavailable under anoxia, a supposition that has not been thoroughly investigated in any soil type. Here, we use anoxic soil reactors amended with and without a chemically defined polyphenol to test this hypothesis, employing metabolomics and genome-resolved metaproteomics to interrogate soil microbial polyphenol metabolism. Challenging the idea that polyphenols are not bioavailable under anoxia, we provide metabolite evidence that polyphenols are depolymerized, resulting in monomer accumulation, followed by the generation of small phenolic degradation products. Further, we show that soil microbiome function is maintained, and possibly enhanced, with polyphenol addition. In summary, this study provides chemical and enzymatic evidence that some soil microbiota can degrade polyphenols under anoxia and subvert the assumed polyphenol lock on soil microbial metabolism.

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.

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.

Availability and implementation

For kb_DRAM users, the kb_DRAM apps on KBase can be found in the catalog at https://narrative.kbase.us/#catalog/modules/kb_DRAM. For kb_DRAM users, a tutorial workflow with all documentation is available at https://narrative.kbase.us/narrative/129480. For kb_DRAM developers, software is available at https://github.com/shafferm/kb_DRAM.

The deep terrestrial biosphere harbours a substantial fraction of Earth's biomass and remains understudied compared with other ecosystems. Deep biosphere life primarily consists of bacteria and archaea, yet knowledge of their co-occurring viruses is poor. Here, we temporally catalogued viral diversity from five deep terrestrial subsurface locations (hydraulically fractured wells), examined virus-host interaction dynamics and experimentally assessed metabolites from cell lysis to better understand viral roles in this ecosystem. We uncovered high viral diversity, rivalling that of peatland soil ecosystems, despite low host diversity. Many viral operational taxonomic units were predicted to infect Halanaerobium, the dominant microorganism in these ecosystems. Examination of clustered regularly interspaced short palindromic repeats-CRISPR-associated proteins (CRISPR-Cas) spacers elucidated lineage-specific virus-host dynamics suggesting active in situ viral predation of Halanaerobium. These dynamics indicate repeated viral encounters and changing viral host range across temporally and geographically distinct shale formations. Laboratory experiments showed that prophage-induced Halanaerobium lysis releases intracellular metabolites that can sustain key fermentative metabolisms, supporting the persistence of microorganisms in this ecosystem. Together, these findings suggest that diverse and active viral populations play critical roles in driving strain-level microbial community development and resource turnover within this deep terrestrial subsurface ecosystem.

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.

Hydraulic fracturing is one of the industrial processes behind the surging natural gas output in the United States. This technology inadvertently creates an engineered microbial ecosystem thousands of meters below Earth's surface. Here, we used laboratory reactors to perform manipulations of persisting shale microbial communities that are currently not feasible in field scenarios. Metaproteomic and metabolite findings from the laboratory were then corroborated using regression-based modeling performed on metagenomic and metabolite data from more than 40 produced fluids from five hydraulically fractured shale wells. Collectively, our findings show that Halanaerobium, Geotoga, and Methanohalophilus strain abundances predict a significant fraction of nitrogen and carbon metabolites in the field. Our laboratory findings also exposed cryptic predatory, cooperative, and competitive interactions that impact microorganisms across fractured shales. Scaling these results from the laboratory to the field identified mechanisms underpinning biogeochemical reactions, yielding knowledge that can be harnessed to potentially increase energy yields and inform management practices in hydraulically fractured shales.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.