Microbes and their viruses are recently found to be profoundly impacting in virtually any ecosystem studied – from the oceans and soils to humans and bioreactors. While our knowledge of viral diversity is growing, we often observe genomes without knowing which host cell the virus infects. This proposal seeks to leverage ecosystem modeling and high-resolution time series datasets to scalably identify which viruses infect which hosts in experimental model systems and complex communities. Should it be successful, the new analytic will be powerful context for studying viruses in any ecosystem.
Proposer: Matt Sullivan, The Ohio State University
Proposal: Inferring virus-host interactions through multi-omics high-resolution time series