Developing Experimental and Computational Approaches to Characterize Viral Distribution, Spread, and Variant Emergence

• Main Author: Normandin, Erica
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01-01-2022
• Subjects: Virology
• ISBN: 9798819382769

Many viral mutations that impact human pathogenicity arise over the course of disease, yet intrahost viral dynamics remain poorly characterized. Mutations that emerge during infection may confer adaptation for invasion or replication, and can contribute to critical population-level viral evolution. Characterization of viral distribution and the mutations present in multiple tissues not only elucidates the basis of acute tissue-specific pathologies, but also sheds light on the possibility for persistent infection in an anatomical reservoir, which could give rise to lingering symptoms, eventual viral reactivation, and/or sustained accumulation of potentially adaptive viral mutations. I develop refined methods for studying intrahost viral distribution and variation and apply them to natural infections of three distinct RNA viruses: Ebola virus (EBOV), Powassan virus (POWV), and SARS-CoV-2, the causative agent of COVID-19. These workflows focus on robust identification of viral mutations that arise in natural infections, especially through minimizing contamination bias, while maximizing depth of viral sequencing from various tissue samples. For each virus, I observed evidence of infection in multiple organ systems, including in the immune privileged sites; these infections were apparently compartmentalized in each case. The observation of frequent compartmentalized infections in immune privileged sites, across distinct viral families, informs patient care and public health measures; this phenomenon may lead to continued pathology, repeated bouts of disease, and sustained evolution leading to the introduction of novel variants to the population. The workflows I describe may be rapidly applied to further studies.