Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

The Predictive Power of Phylogeny on Growth Rates in Soil Bacterial Communities


Jeth Walkup1* (, Ember M. Morrissey1, Chansotheary Dang1, Rebecca L. Mau2, Michaela Hayer2, Egbert Schwartz2, Bram W. Stone3, Kirsten S. Hofmockel3, Benjamin J. Koch2, Alicia M. Purcell2,4, Jennifer Pett-Ridge5,6, Chao Wang8, and Bruce A. Hungate2


1West Virginia University; 2Northern Arizona University; 3Pacific Northwest National Laboratory; 4Texas Tech University; 5Lawrence Livermore National Laboratory; 6University of California–Merced; and 7Chinese Academy of Sciences


Microorganisms are major engines of the land carbon cycle, responsible for influencing the composition and radiative properties of the atmosphere, and for both creating and consuming soil organic carbon, a resource that provides multiple ecosystem services, and, when lost, exacerbates climate change. This project investigates the interactions within microbial communities and between microbes and their environment that underpin these dual roles of microorganisms in creating and consuming soil carbon. Overarching objectives are to develop and apply omics approaches to investigate microbial community processes involved in carbon and nutrient cycling, develop community and taxon-specific microbial controls over key biogeochemical processes in terrestrial environments, and test quantitative ecological and biogeochemical principles using omics data. This work aims to facilitate scaling of taxon-specific microbial data to connect the ecology of microorganisms with ecosystem level rates of carbon and nutrient cycling.


Predicting ecosystem function is critical to assess and mitigate the impacts of climate change. Quantitative predictions of microbially mediated ecosystem processes are typically uninformed by microbial biodiversity. Yet new tools allow the measurement of taxon-specific traits within natural microbial communities. There is mounting evidence of a phylogenetic signal in these traits, which may support prediction and microbiome management frameworks. Researchers investigated phylogeny-based trait prediction using bacterial growth rates from soil communities in Arctic, boreal, temperate, and tropical ecosystems. Here, research shows that phylogeny predicts growth rates of soil bacteria, explaining up to 58% of the variation within an ecosystem. Despite limited overlap in community composition across these ecosystems, shared nodes in the phylogeny and ancestral trait reconstruction allowed cross ecosystem predictions, which showed that phylogenetic relationships can explain up to 38% of the variation in growth rates across biomes. Results suggest that shared evolutionary history creates similarity in the relative growth rates of related bacteria in the wild, allowing phylogeny-based predictions to explain a significant amount of the variation in taxon-specific functional traits, within and across ecosystems.

Funding Information

This research was supported by the DOE Office of Science, Biological and Environmental Research (BER) Program, grant no. DE-SC0020172 and DE-SC0016207. Work at LLNL was performed under the U.S. Department of Energy Contract DE-AC52-07NA27344 and Awards SCW1590 and SCW1679.