bioRxivMicrobiologyPreprint
A functional microbiome catalog crowdsourced from North American rivers
M. A. Borton, B. B. McGivern, K. R. Willi, B. J. Woodcroft, A. C. Mosier, D. M. Singleton, T. Bambakidis, A. C. Pelly, F. Liu, J. N. Edirisinghe, J. P. Faria, I. Leleiwi, R. A. Daly, A. E. Goldman, M. J. Wilkins, E. Hall, C. Pennacchio, S. Roux, E. A. Eloe-Fadrosh, S. P. Good, M. B. Sullivan, C. S. Henry, E. M. Wood-Charlson, M. R. Ross, C. S. Miller, , K. C. Wrighton
Abstract
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 Concept1, 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 cyberinfrastructures2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.
- assay: metagenomics
- research focus: ecology & biodiversity
- research focus: database / resource
- research focus: benchmarking
- research focus: spatial domain detection
- approach: experimental assay
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