Date of Degree

6-2022

Document Type

Dissertation

Degree Name

Ph.D.

Program

Biology

Advisor

Weigang Qiu

Committee Members

Christopher Blair

Mandë Holford

Michael J. Hickerson

Sherwood Casjens

Subject Categories

Bioinformatics | Evolution | Genomics | Other Immunology and Infectious Disease | Population Biology

Keywords

Comparative genomics, Microbial genome evolution, Lyme disease, SARS-CoV-2, Maximum antigen diversification, Centroid Algorithm

Abstract

We live in an era of emerging infectious diseases that are increasingly common, rapidly spreading, and gravely devastating. Lyme disease, caused by bacteria belonging to the genus Borreliella, is rapidly rising in the Northern Hemisphere because of geographic range expansion of both the tick vectors and the pathogens. Evolutionary comparative analysis of Borreliella genomes is a key to understanding the phylogeographic history and mechanisms of their global diversification. Moreover, genomic variations in Borreliella associated with human pathogenicity, e.g., at loci encoding cell-surface antigens interacting with the vertebrate hosts, have not been fully identified. Similarly, the ongoing COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is bringing unprecedented loss of human lives and turmoil in global economic and social orders. While the genome of SARS-CoV-2 coronavirus causing the COVID-19 pandemic is rapidly evolving during the global pandemic, it is not clear how to distinguish the most consequential mutations, such as those associated with human virulence and immune escape, among the numerous genomic changes elsewhere.

By analyzing the genomic sequences of microbial pathogens in an evolutionary framework, I reconstructed biogeographic histories of Lyme disease pathogens. My studies identified that evolutionary mechanisms of SARS-CoV-2 genome diversification driven by natural selection including escape from host immunity. I also implemented novel evolution-informed strategies to combat pathogen diversification.

In chapter 1, I report forty-four newly completed genomes of nineteen Borreliella species from across the world, a comprehensive biogeographic history of their global diversification, and a highly dynamic and fluid plasmid composition and structure mediated by rapid gene duplication, losses, and translocation. In chapter 2, I show that Lyme disease-causing bacterium Borreliella burgdorferi produces an outer surface protein C (OspC) that displays high antigenicity specificity. To overcome the challenge of OspC antigenic diversity in the development of preventive clinical vaccine strategies, I report evolution-inspired designs of synthetic antigens that are more broadly reactive than the natural OspC variants. These synthetic evolutionary analogs of OspC showed promise as diagnostic and vaccine candidates against diverse pathogen strains coexisting in the endemic areas of Lyme disease in the United States. Our automated evolution-based computational design opens a novel path to combating other fast-evolving microbial pathogens as well.

In chapter 3, I report an evolutionary analysis of close to one million SARS-CoV-2 genomes and show that a key signature of human-adaptive mutations is their tendency to form clusters of shared allelic frequency trajectories over time. Furthermore, my colleagues and I have developed novel software tools including a database, a bioinformatics pipeline, a genome-evolution simulator, and a web interface to facilitate rapid identification of genomic signatures of viral adaptation to humans during the current and future viral outbreaks.

In combination, these chapters offer a comprehensive understanding of key drivers of adaptive genome evolution of two major microbial pathogens, provide a set of software tools and pipelines for analyzing microbial genome variability, and propose an evolution-based strategy to combat pathogen diversification.

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