Applying third-generation sequencing to pathogen surveillance and mixed infection detection

Abstract

One Health is the concept of interconnected health between plants, animals, humans, microorganisms and the environments they live in. One Health issues surround many important viral pathogens, including influenza, SARS-CoV-2, and Ebola, that have likely come from zoonotic spillovers. Genomic epidemiology combines pathogen genomes with metadata to forecast, track, and prepare for future pathogens and pathogen variants that may cause epidemics. Genomic epidemiology has been used to detect and track viral variants that have the potential to escape vaccines for viruses like porcine circovirus type 2 (PCV2). PCV2 causes porcine circovirus associated diseases (PCVAD), which results in weight loss and death in pigs around the world. The correlation between PCVAD and mixed infections shows that disease severity is linked to the microbial community in a host. Metagenomics allows researchers to sequence samples and sort out the individual community member genomes by bioinformatic analyses, allowing the study of the host microbiome. In this thesis, I tested if long read nanopore sequencing can uncover PCV2 diversity and reliably detect co-infections. I also assessed the accuracy and efficiency of long read metagenomic assemblers as a potential method for detecting mixed infections. In my first chapter, I found that nanopore sequencing can be used to understand PCV2 diversity and detect co-infections. This evidence shows that nanopore sequencing is a viable alternative to Sanger sequencing for PCV2 surveillance. In my second chapter, I found Flye built the most complete and accurate genomes for bacterial community members and their plasmids. Throughout my thesis I have shown that nanopore sequencing is a viable solution for modern surveillance. The lower cost of nanopore sequencing may allow more specific pathogen and metagenomic surveillance in regions with high risk of zoonotic spillovers, which may allow early detection of epidemic causing pathogens.