Development of Next-Generation DNA Sequencing Enabled Pathogen Detection

Detection and mitigation of environmentally transmitted pathogens, microorganisms that cause disease, is necessary to ensure the protection of public health. There exists a great diversity of known pathogens, and untold diversity of unknown pathogens, in the world. Many pathogens cannot be detected by traditional methods, and all existing methods are limited by the ability to only detect a small subset of pathogens, hindering our ability to understand pathogen diversity in the environment. The goal of the research presented in this dissertation is to demonstrate the importance of considering pathogen diversity in regulation and risk assessment and to develop a target-independent method of identifying pathogen diversity in environmental samples. To demonstrate the necessity of including all pathogens in risk assessment, an aerosol transport model of sewage sludge land application was updated to include non-regulated pathogens. Predicted risk for non-regulated pathogens was orders of magnitude higher than those that are regulated and for which monitoring is required. Additionally, predicted risk from viruses was higher than that from bacteria, despite that fact that viruses have not traditionally been a focus of pathogen regulation in sewage sludge.;Metagenomics, the random sequencing of environmentally derived DNA fragments, coupled with emerging DNA sequencing technologies, has the potential to identify all highly enriched pathogens in an environmental sample. This technique was applied to study both bacterial and viral pathogens in sewage sludge. For bacterial pathogens, the 16S rDNA gene was amplified, sequenced, and annotated. Potential pathogens were identified to be less than 0.1% of bacterial sequences, and the vast majority was shown to be opportunistic pathogens. Additionally, at the sequencing level achieved, there was not a significant difference between sewage sludge and soil in pathogen content, but sewage sludge was more highly enriched in human microbiota, such as Enterococcus. For viral pathogens, both shotgun and gene targeted metagenomic approaches were applied. Prior to sequencing, an in silico study demonstrated the most appropriate annotation scheme for shotgun metagenomics to be tBLASTx against a viral-only genome database with a cutoff E-value of 0.001. Both initial and larger-scale follow up sequencing efforts were successful at identifying viral pathogens. Somewhat surprising, among the most abundant pathogens identified were the emerging Picornaviruses parechovirus and klassevirus, suggesting a potential role in sewage sludge related disease and also their potential as source tracking organisms. Adenovirus hexon gene sequencing identified subgroups B and C, typically associated with respiratory disease, to be the most abundant. This work also demonstrated differential inactivation behavior between RNA and DNA viruses, suggesting that updated monitoring requirements include both RNA and DNA viruses.;This work demonstrated that consideration of pathogen diversity is necessary to understand risk, current approaches underestimate pathogen risk in the environment, and that metagenomics is an effective method to better understand pathogen diversity.