OPS 2-17
Microbial ecological process models developed using National Ecological Observatory Network (NEON) metagenomic and metatranscriptomic data

Tuesday, August 6, 2013
Exhibit Hall B, Minneapolis Convention Center
William Rodriguez, Graduate Program in Organismic and Evolutionary Biology, University of Massachusetts, Amherst, Amherst, MA
Monique Tait, Microbiology, University of Massachusetts, Amherst, MA
Sonia Filipczak, Biology, University of Massachusetts, Amherst, MA
Jeffrey L. Blanchard, Biology, University of Massachusetts, Amherst, Amherst, MA
Background/Question/Methods

Terrestrial ecosystems play a major role in controlling and steering the flow of the carbon cycle. Three quarters of the carbon in terrestrial ecosystems is found as organic matter in soils, most of which is derived from plants. Microbial digestion of plant detritus forms the basis for carbon transformations in soil, yet the complex relationships between plants and diverse soil microbes are not well understood. The ability to predict rates of substrate utilization, sequestration of stable organic molecules, and the release of greenhouse gases such as carbon dioxde and methane, which impact climate, depends on a deeper understanding of the interactions between microbial community members, their utilization of plant detritus and subsequent feedbacks on plant growth. Our ability to understand carbon cycling by microbial communities is being transformed by rapid advances in DNA sequencing technology. Metagenomic and metatranscriptomic data provides a foundation for an exciting “reverse ecology” framework for determining underlying networks of interactions within microbial communities.

Results/Conclusions

We have developed strategies to effectively integrate computational analyses of species diversity and microbial function, in order to understand how communities differ. Analyses will be presented of microbiome data from National Ecological Observatory Network (NEON) prototype experiments with an emphasis on metabolic pathways involved in biogeochemical cycling.