The rapid evolution of RNA viruses makes them particularly challenging targets for vaccines and antiviral drugs. However, a clearer understanding of their unique evolutionary dynamics may suggest novel approaches for control. Our research objective is to understand mechanisms of viral evolution as they relate to transmission and pathogenesis in infected hosts. We study aspects of evolutionary theory in the context of the host-pathogen interface using molecular virology, small animal models, and sequence data from clinical specimens.
We are particularly interested in aspects of mutation rate and mutational tolerance in poliovirus, influenza, and other RNA viruses. These viruses have extremely high mutation rates, which ensures that the vast majority of newly replicated genomes will be genetically distinct. High mutation rates are clearly a mixed blessing, however, since work in a number of systems indicates that most mutations are either lethal or highly detrimental to viral fitness. Therefore, a virus’ ability to buffer the negative impact of mutation may be an important contributor to its overall fitness. Consistent with this model, we have found that codon usage can influence the mutational robustness of poliovirus, its fitness in vitro, and its ability to spread within an infected host. More recently, we have studied the mutational tolerance of influenza virus and found that transversion mutations are generally more damaging than transitions.
Our findings of mutational hypersensitivity in RNA viruses have led us to re-examine models of mutation rate evolution. Since most mutations are deleterious and mutation rates are tuned by natural selection, why hasn’t the virus evolved to have a lower mutation rate? To answer this question, we have developed a novel assay for viral mutation rates that provides precise measurements for the rates of each mutational class (A to G, U to C etc.). We have used experimental evolution of poliovirus to show that high mutation rates are not in themselves adaptive for the virus. Rather, our data indicate that viral mutation rates are driven higher as a result of selection for viruses with faster replication kinetics. We suggest that viruses have high mutation rates because fidelity imposes a high energetic cost.
Our studies of mutation rates have led us to develop a number of methods for measuring viral diversity within hosts, which we are now using to understand influenza virus dynamics in natural human infections. We have developed and empirically validated a next generation sequencing analysis pipeline to identify intrahost single nucleotide variants at ≥1% frequency in clinical specimens with ≥99.9% specificity. We have used this pipeline to analyze viruses collected as part of a randomized, placebo-controlled trial of vaccine efficacy. This large study of natural infections over 5119 person-years of observation defined the impact of vaccine-induced immunity on intrahost populations. Building on this success, we have an ongoing collaboration with colleagues at the School of Public Health to use deep sequencing of viruses from individuals in a household cohort to infer transmission events and to quantify the transmission bottleneck for respiratory viruses. By defining key population genetic parameters for influenza viruses in natural human infections, we hope to inform models of viral spread in households and communities.