Within-host RNA virus evolution in the context of cellular coinfection and genetic linkage Open Access

Abstract

RNA viruses pose one of the greatest threats to public health, in part due to their rapid evolutionary patterns. As viruses infect individuals in a population they accrue mutations, some of which confer phenotypes that increase the virulence or transmissibility of the virus. While these phenotypes can have population-level consequences, the evolutionary forces that allow adaptive mutations to reach high frequency largely occur at the level of individual hosts. Further, the dynamics that ensue at the host-level are consequences of processes at the intra- and inter-cellular levels. I explore how the diversity of within-host viral populations is shaped, with particular considerations for cellular coinfection and genetic linkage. When viruses coinfect host cells, different parental genotypes produce protein products by hijacking host cell machinery and these proteins help to produce progeny virions. We ask what happens when proteins with differential fitness effects are treated as public goods. A key assumption of our models is that when coinfection occurs, the fitness of the viral progeny is a result of incomplete dominance from the parental genotypes. This results in fitness that is in between the most- and least-fit parents. We develop models and apply them to data to investigate the evolutionary phenomena that result from these within-host scenarios. Using simulations, we show that coinfection weakens the efficacy of selection, approaching the neutral selection limit. So as rates of coinfection increase, so do rates of deleterious mutation accumulation. We also develop deterministic models of wild-type and mutant virus evolution within-host. We show that a beneficial mutant is fixed less readily when we increase rates of coinfection. We then use Markov chain Monte Carlo to infer the relative fitness of a viral mutation that occurred in an animal model of influenza infection. These contributions are significant because we know that coinfection occurs within-host, and our work shows that models that infer fitness without considering coinfection are likely underestimating the magnitude of fitness coefficients. Our results may help to explain slower fixation of adaptive variants at the epidemiological level. Next, we identify intra-host single nucleotide variants (iSNVs) in immunocompromised patients with chronic SARS-CoV-2 infections. Experimental collaborators show that some of these iSNVs confer immune escape induced by monoclonal antibody treatment. Finally, we investigate interpretations of within-host evolution with data from a focal patient. We show that iSNV data alone can lead to incomplete evolutionary narratives, but additional resolution can be obtained when genetic linkage through haplotype analysis is brought to the fore.

Table of Contents

Introduction 1 Heterogeneity in viral infections increases the rate of deleterious mutation accumulation 5 Abstract 6 Introduction 6 Model 8 Base model 8 Heterogeneous cellular output stemming from differences in cellular characteristics 11 Heterogeneous cellular output stemming from differences in cellular multiplicity of infection 12 Alternative fitness functions 12 Results 13 Phenotypic hiding relaxes selection 13 Stochastic heterogeneity increases deleterious mutation accumulation 18 Input-dependent viral populations accumulate slightly more deleterious mutations at intermediate MOI 21 Relaxed selection under phenotypic hiding is robust to the form of the fitness function 21 Discussion 23 Appendix A. Supplementary Materials to Chapter 2 28 Base Model Comparison Against Gordo and Charlesworth (2000) 29 Stochastic Heterogeneity 30 Input-Dependent Heterogeneity 31 Stochastic Heterogeneity Impacts Are Consistent Across Alternative Fitness Functions 32 Simulated mutations are assumed to be "dominant" 32 Simulated mutations are assumed to be "recessive" 33 Fitness estimation for viral variants in the context of cellular coinfection 34 Detecting intra-patient single nucleotide variants of SARS-CoV-2 in chronically infected immunocompromised patients 51 Haplotypes are more informative than iSNVs when interpreting the evolutionary dynamics of SARS-CoV-2 within an immunocompromised host 87 Abstract 89 Introduction 90 Methods 92 Data 92 Calling of intrahost single nucleotide variants 93 Reconstruction of haplotypes 95 Results 95 iSNVs appear to indicate multiple targets of selection 96 Haplotype reconstruction casts doubts on independent selection on individual iSNVs and points towards the role of within-host reservoirs 98 Discussion 105 Conclusion 108 Bibliography 111

About this Dissertation

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School	Laney Graduate School
Department	Biological and Biomedical Sciences
Subfield / Discipline	Population Biology, Ecology & Evolution
Degree	Ph.D.
Submission	Dissertation
Language	English
Research Field	Biology, Evolution and Development Biology, Virology
Keyword	virus evolution evolutionary biology computational biology within-host dynamics influenza A virus SARS-CoV-2
Committee Chair / Thesis Advisor	Daniel Weissman, Emory University Katia Koelle, Emory University
Committee Members	Levi Morran, Emory University Tim Read, Emory University Anice Lowen, Emory University

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