I-Corps: Next-Gen Diagnostics

George Washington University, Washington DC

Investigators

Abstract

Researchers have developed a sequencing application and associated bioinformatics techniques to rapidly and accurately identify pathogens. Data and samples are analyzed using the research team's bioinformatic approach that uses a Bayesian reassignment model to accurately identify pathogens to a known database with 1) high accuracy, even 2) with low coverage, and 3) with mixed samples, 4) no need for sequence assembly, and 5) report back not only accurate species diagnostics, but also relevant information on antibiotic/antiviral resistance mutations. Most approaches currently used rely on old microbiology techniques for growing cultures from samples (a week long process) and identifying pathogens through visual inspection. This approach has the added advantage, because it is a genomic approach, of also providing insights into drug resistance through the identification of drug resistant variants thus better informing treatment options. Accurate and rapid pathogen diagnostics is critical to a number of areas of commercial importance including food safety, human health, and veterinary medicine. This approach has the potential to revolutionize pathogen diagnostics in multiple areas including food safety, hospital hygiene, veterinary care, and human health. The approach used by the research team has the potential to be more rapid, accurate, and cost-effective. It capitalizes on next-generation sequence data to characterize the diversity and extent of pathogen infection.