Construction of a Microbial Methane Observatory Reveals Metabolic Dynamics of Freshwater Wetland Microbiomes
Authors:
Mikayla Borton1, Angela Oliverio1,2*, Jared Ellenbogen1, Brooke Stemple1, Rory Flynn1, Bridget McGivern1, David Hoyt3, Jorge Villa4, Christopher Miller5, Gil Bohrer6, Timothy Morin7, and Kelly Wrighton1
Institutions:
1Colorado State University; 2Syracuse University; 3Pacific Northwest National Laboratory; 4University of Louisiana; 5University of Colorado; 6The Ohio State University; and 7State University of New York College of Environmental Science and Forestry
Goals
This project interrogates microbial contributions to carbon cycling in soils from a freshwater, coastal wetland adjacent to Lake Erie, OH. This site was selected as it has the highest annual methane fluxes within the AmeriFlux network. To profile the microbial contributions to methane release the team instrumented the wetland with in situ porewater and greenhouse gas (GHG) flux (i.e., CO2 and CH4) measurements and flux tower for site-wide flux measurements. A first goal of this project required construction of a microbial genome-resolved database generated to interrogate microbial physiological contributions to wetland GHG fluxes. Secondly, the team developed computational application in the annotation software Distilled Refined Annotation of Metabolism (DRAM) to profile the microbial traits in this genomic database. Lastly, the team mapped metatranscriptomes collected from temporal sampling and highly spatially resolved sampling to resolve expressed microbial community metabolic traits over years, within seasons, and along centimeter depth to meter land-coverage gradients. Leveraging the multiomics data in conjunction with geochemical, metabolomic, and GHG measurements, researchers provide unprecedented insight into how hydrological perturbations impact methane flux from a coastal, freshwater wetland.
Abstract
Freshwater wetlands contribute over a third of global methane emissions and store 30% of global soil carbon, which may become increasingly available for microbial degradation into GHGs. Despite their global climatic significance, it remains difficult to establish a mechanistic understanding of the microbial controls on soil biogeochemical processes, limiting the ability to predict GHG emissions. Here, researchers built a comprehensive catalog of 17,333 metagenome-assembled genomes representing 2,502 dereplicated genomes spanning 72 phyla from freshwater wetlands, of which 57% represent novel lineages with no genomic representation. The team then coupled its wetlands genome database with 133 genome-resolved metatranscriptomes and highly resolved compositional and geochemical profiling of over 700 samples to identify the dominant axes of environmental variation shaping the composition and transcription of microbial genomes in the wetlands system. Researchers further delineate the contributions of major microbial lineages to biogeochemically relevant processes including methanogenesis, sulfate reduction, and denitrification.
Although soil methanogens and methanotrophs have been cultivated for decades, the project’s genome recovery approach resulted in 88 methanogen genomes representing all methanogenic pathways. These include three novel families, 17 novel genera, and for some taxa, the first genomes identified in a wetland environment—illuminating the phylogenetic and metabolic diversity harbored in terrestrial ecosystems. First, the team used NMR-metabolites to survey the distribution of methanogenic substrates across the wetland; with flooding, researchers observed increases in methanogen substrates of acetate and methanol only in the surface soils. Concomitant with increased availability of these substrates, the team observed gene activity from methanogens utilizing acetate and methanol in these surfaces increased 4.9 and 1.6-fold respectively with flooding. This expanded substrate availability, and concentrations likely contributed to the nearly 5-fold increase in methane production reported in the surface soils with flooding. Surprisingly, while researchers expected the shift to anoxia with flooding would decrease aerobic methanotrophy in surface soils, gene expression data indicated aerobic methanotrophs metabolized methane using very low oxygen concentrations. Team members also demonstrated the first gene expression data evidence for nitrate-enabled methanotrophy in soil systems. Given that methanol utilizing methanogens and anaerobic methanotrophs are currently not accounted for in climate models, the findings show important data add increased realism to biogeochemical models of terrestrial methane emissions.
Using co-expression network analysis, the team revealed coordinated, active microbial neighborhoods that are localized to depth but stable across months, seasons, and years. These microbial guilds are predictive of in situ GHG concentrations. Using integrated metabolite and metatranscriptome data researchers reconstructed the metabolic circuitry explaining a substantial fraction of variability in these GHGs. Findings link biogeochemical shifts to the genome transcription of specific microbial lineages and processes and begin to establish an integrative framework for leveraging high-dimensional multiomics data towards process-based models of the ecology and biogeochemistry of freshwater wetlands.
Funding Information
This research was supported by the DOE Office of Science, Office of Biological and Environmental Research (BER), grant no. DE-SC0023084. This program is supported by the U.S. Department of Energy, Office of Science, through the Genomic Science Program, Office of Biological and Environmental Research, under FWP ERKP123.