Viable pathogen identification using metatranscriptomics and machine learning in microbial risk assessment

Funding period: 2020-2024
Lead: Derek Smith
Total GRDI funding: $125,000

This project is developing next generation sequencing and analysis methods to identify viable pathogens present in mixtures/consortia and the environment. Existing sequencing and molecular biology methods struggle to identify pathogens with sufficient resolution to distinguish them from closely related non-pathogens and do not provide reliable information on viability. We propose to sequence the short-lived RNA molecules that are actively produced only in viable cells. This sequencing method can be used for accurate typing of organisms through the identification of multiple marker genes and allows for the quantification of gene activity in microbial communities. It focuses on the prevalence and activity of virulence factors, which can be used through computational learning to inform environmental and health risk assessments.