Intergenerational phenotypic mixing in viral evolution

Beneficial coinfection can promote within-host viral diversity

In many viral infections, a large number of different genetic variants can coexist within a host, leading to more virulent infections that are better able to evolve antiviral resistance and adapt to new hosts. But how is this diversity maintained? Why do faster-growing variants not outcompete slower-growing variants, and erode this diversity? One hypothesis is if there are mutually beneficial interactions between variants, with host cells infected by multiple different viral genomes producing more, or more effective, virions. We modelled this hypothesis with both mathematical models and simulations, and found that moderate levels of beneficial coinfection can maintain high levels of coexistence, even when coinfection is relatively rare, and when there are significant fitness differences between competing variants. Rare variants are more likely to be coinfecting with a different variant, and hence beneficial coinfection increases the relative fitness of rare variants through negative frequency dependence, and maintains diversity. We further find that coexisting variants sometimes reach unequal frequencies, depending on the extent to which different variants benefit from coinfection, and the ratio of variants which leads to the most productive infected cells. These factors could help drive the evolution of defective interfering particles, and help to explain why the different segments of multipartite viruses persist at different equilibrium frequencies.

Modelling the emergence of influenza drug resistance: The roles of surface proteins, the immune response and antiviral mechanisms

The emergence of influenza drug resistance has become of particular interest as current planning for an influenza pandemic involves using massive amounts of antiviral drugs. We use semi-stochastic simulations to examine the emergence of drug resistant mutants during the course of a single infection within a patient in the presence and absence of antiviral therapy. We specifically examine three factors and their effect on the emergence of drug-resistant mutants: antiviral mechanism, the immune response, and surface proteins. We find that adamantanes, because they act at the start of the replication cycle to prevent infection, are less likely to produce drug-resistant mutants than NAIs, which act at the end of the replication cycle. A mismatch between surface proteins and internal RNA results in drug-resistant mutants being less likely to emerge, and emerging later in the infection because the mismatch gives antivirals a second chance to prevent propagation of the mutation. The immune response subdues slow growing infections, further reducing the probability that a drug resistant mutant will emerge and yield a drug-resistant infection. These findings improve our understanding of the factors that contribute to the emergence of drug resistance during the course of a single influenza infection.

Suppression of Drug Resistance in Dengue Virus

Dengue virus is a major human pathogen responsible for 400 million infections yearly. As with other RNA viruses, daunting challenges to antiviral design exist due to the high error rates of RNA-dependent RNA synthesis. Indeed, treatment of dengue virus infection with a nucleoside analog resulted in the expected genetic selection of resistant viruses in tissue culture and in mice. However, when the function of the oligomeric core protein was inhibited, no detectable selection of drug resistance in tissue culture or in mice was detected, despite the presence of drug-resistant variants in the population. Suppressed selection of drug-resistant virus correlated with cooligomerization of the targeted drug-susceptible and drug-resistant core proteins. The concept of “dominant drug targets,” in which inhibition of oligomeric viral assemblages leads to the formation of drug-susceptible chimeras, can therefore be used to prevent the outgrowth of drug resistance during dengue virus infection.

Drug resistance is a major hurdle in the development of effective antivirals, especially those directed at RNA viruses. We have found that one can use the concept of the genetic dominance of defective subunits to “turn cousins into enemies,” i.e., to thwart the outgrowth of drug-resistant viral genomes as soon as they are generated. This requires deliberate targeting of larger assemblages, which would otherwise rarely be considered by antiviral researchers.

Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection

Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.