Putting microorganisms on the map: continental-scale context for thousands of newly sampled microbial genomes from North American watersheds
Abstract
Gaining an understanding of the spatial and temporal drivers of freshwater microbiomes and their responses to environmental change is of critical importance. These microorganisms recycle and transform nutrients, control greenhouse gas fluxes, and are the basis of food webs that maintain ecosystem homeostasis in fluvial systems. Despite these vital roles, microbial knowledge is often limited to taxonomic identity alone and rarely includes cross-site comparisons. Addressing the fundamental question of how bacterioplankton community composition and metabolic function varies across river basins in the continental United States required a coordinated, community science effort reliant on collaborations with over 150 scientists, an engagement that facilitated the sampling of 221 surface water samples in the continental United States. Microbiomes from all sites were characterized using genome resolved metagenomics, offering an unprecedented sampling of the microbial strains and their functional contributions to river biogeochemistry. To openly share this content, we created a first-of-its-kind resource known as the Genome Resolved Open Watershed (GROW) database. This contains the identity and distribution of thousands of unique microbial genomes and includes a corresponding catalog of over 2 million microbial genes, including a sampling of 850 genes with known capacity to modulate carbon, nitrogen, sulfur, and hydrogen cycling in these watersheds. Approximately a third of the samples have paired metatranscriptomes and metabolomes, distinguishing active from latent microbial processes along hydrological regimes. The breadth of important ecological dimensions included in this work (e.g. stream order, chemistry, physical network, land use) enabled us to systematically identify the most cosmopolitan microbiome members from within the Proteobacteria, Actinobacteria, and Bacteroidetes, while also revealing local drivers of strain specific endemism. GROW is a living road map, articulating the power of community science to decode microbial organismal and metabolic distribution patterns at scales necessary for ingestion into predictive modeling frameworks.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.B22A..09W