PurSUiT: Unveiling microbial eukaryotic melting-pots: virus emergence via RNA-DNA gene transfer.

The origin of viruses and how they evolve is poorly understood. DNA viruses, like herpesviruses, were thought to evolve completely separately from RNA viruses, like flu. Recently discovered cruciviruses that appear to have evolved from both RNA and DNA viruses challenge that thought. This project seeks to understand the evolution of cruciviruses by developing biotechnological and Artificial Intelligence (AI) tools to 1) discover cruciviruses in environmental samples, and 2) isolate the microbes that they infect. Beyond advancing the understanding of virus evolution, this work serves the national interest by creating technologies with potential broader applications including detection and prediction of future viral pandemics. Furthermore, this research will strengthen our future biotechnology workforce through training, and inform the general public through outreach events. This project is focused on the targeted discovery of cruciviruses and related RNA-viruses, and their eukaryotic host microorganisms in environmental samples to assess patterns of horizontal gene transfer in virus evolution. This will be done by pursuing three research aims. First, it will establish an ecological framework for DNA/RNA gene exchange. Novel molecular enrichment techniques will preferentially amplify cruciviruses and related RNA-viruses, DNA-viruses and plasmids in soil, fresh- and sea water, and hot spring samples. Second, the project will identify crucivirus-infected protists from environmental samples. Fluorescence-activated cell sorting on samples will be used to detect associations of cruciviruses with host organisms. The isolation of a host-crucivirus pair will allow exploration of the molecular mechanisms and in vivo analysis of RNA-DNA gene transfer and identify new protists and their viruses. Finally, the project will determine the origin and evolution of cruciviruses using sequence analysis. Multipartite network analysis and machine learning (AI) trained for virus-type recognition will be used to model the evolutionary history of cruciviruses. This will allow an examination of their possible role in de novo virus emergence. These three aims will enhance our understanding the origin of ubiquitous, poorly understood circular single-stranded DNA viruses, and the evolution and mechanisms of gene transfer between RNA and DNA viruses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2548508 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Kenneth Stedman | Institution: Portland State University, PORTLAND, OR | Award Amount: $1,020,345 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2548508 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2548508.html