Rapid advances in DNA sequencing enable new ways to study the microorganisms that mediate key processes in human health, engineered systems, and natural environments. However, emerging approaches are limited by lack of effective methods for analyzing large sequence datasets in the context of metadata. This project will bring together PIs from biology, environmental science, and statistics to develop new approaches for integrated analysis of omics and environmental data from microbial communities. We will leverage recent datasets from weekly samples of Lake Erie cyanobacterial harmful algal blooms to advance in parallel (i) organization of data via a new graph database, and (ii) statistical analysis of gene content and expression with respect to environmental parameters. These results will reveal environmental controls on cyanobacterial blooms, which threaten drinking water supplies, and produce tools that are widely applicable to analysis of large omics datasets from microbiomes.
The role of heterotrophic bacteria in protecting cyanobacteria from hydrogen peroxide in coastal systems
$874,085 from the National Science Foundation.
Genome sequences of lower Great Lakes Microcystis sp. reveal strain-specific genes that are present and expressed in western Lake Erie blooms
Published in PLOS One.