Thursday, October 11 2018
10:55am
Room 1005, Roger A. and Helen B. Krone Engineered Biosystems Building (EBB), 950 Atlantic Dr NW, Atlanta, GA 30332
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Dynamics of Microbial Populations and Biogeochemical Processes Impacting Aquatic Dead-Zones

Sarah Preheim, Ph.D.
Department of Environmental Health and Engineering
Johns Hopkins University

Abstract
Pollution from agricultural and urban areas fuels excessive algae and cyanobacteria growth, resulting in low oxygen dead-zones during decomposition. These microbial processes deteriorate water quality, reduce the habitat of many economically important aquatic animals and drive biogeochemical processes that alter nutrient cycling and generate potent greenhouse gases. Since population growth and climate change are expected to exacerbate these problems, understanding the dynamic chemical and microbial changes that impact aquatic dead-zones will aid modeling efforts that guide remediation strategies. I will present work to 1.) improve our understanding of the relationship between genes, populations and biogeochemical processes to improve predictive biogeochemical models and 2.) identify viral infections that contribute to cyanobacteria mortality with a novel high-throughput, culture-independent method, epicPCR. To investigate the relationship between microbial genes, populations and the biogeochemical processes they mediate, we used genome reconstruction from metagenomic data and a previously developed biogeochemical model to identify microbial populations implicated in major biogeochemical transformations in a model lake ecosystem. By reconstructing microbial genomes from complex assemblages of microorganisms, we gained insight into microbial processes in the lake and identified additional biogeochemical processes previously omitted from the model that could significantly alter the predicted biogeochemistry of the lake if active. We are also investigating the relationship between microbes, their genes and model predictions in a more complex ecosystem, the Chesapeake Bay. Viral infections will also be identified in the Chesapeake Bay through epicPCR. Identifying populations under the most viral pressure in the environment can improve models of biogeochemical cycling, providing a holistic picture of viruses in the trophic structure of marine environments. Yet, these efforts are stalled because the specific host a virus infects remains largely unknown for a majority of observed viruses. We hope to identify infections that contribute to ecological shifts and alter biogeochemical processes with our to high-throughput, culture-independent approach. Although this method is currently under development, preliminary data suggests the approach can identify specific infections in the environment and reveal the complex network of viral infections in natural microbial communities.

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