66 Utilizing Third Generation Sequencing to Identify Pathogen Outbreaks Rapidly and Accurately. (12th April 2022)

• Record Type: Journal Article
• Authors: Neujahr, Alison; Loy, Duan; Loy, J Dustin; Brodersen, Bruce; Fernando, Samodha
• Is Part Of: Journal of animal science. Volume 100(2022)Supplement 2
• Page Start: 28
• Page End: 28
• Publication Date: 2022-04-12
• Subjects: outbreak -- Oxford Nanopore MinION Technology -- virus; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/skac064.045
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: The temporal trend of novel pathogen identification has increased over the last decade, with viruses being the main contributor to the increase. Currently, the NAHLN provides veterinary surveillance and testing procedures for high consequence animal diseases, where in many cases, the detection of these diseases is based on real-time PCR assay (ASF, CSF, FMD, and IAV-S) or pathogen specific antibodies using ELISA methods (PRV). However, genetic shift and drift in virus genomes can lead to failure in detection of novel or emerging pathogens. Therefore, with the current trend of increased viral disease emergence, novel methods are needed to accurately and rapidly identify and characterize viral pathogens independent of knowing genomic information. In this study, we developed a novel diagnostic approach to identifying swine pathogens, using surrogate viruses. We implemented the use of Oxford Nanopore MinION Technology to detect long read sequences in real time. Surrogate viruses were used in place of common pathogens such as African Swine Fever, Classical Swine Fever, Pseudorabies, Foot and Mouth Disease, and Influenza A to investigate rapid detection limits. To increase the complexity of a sample, both DNA and RNA viruses were spiked into tissues were analyzed using Oxford Nanopore MinION Technology. This method can detect both DNA and RNA viruses simultaneously without prior knowledge. Additionally, as sequences can be detected real-time, we were able to confidently detect viral pathogens within a sample within 30 min. Additionally, we have established a library preparation and sequencing protocol as well as an informatic pipeline that could allow clinics and diagnostics centers to identify pathogens in less than 10 hours.