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A large number of medically important viruses, including HIV, hepatitis C virus, and influenza, have RNA genomes. These viruses replicate with extremely high mutation rates and exhibit significant genetic diversity. This diversity allows a viral population to rapidly adapt to dynamic environments and evolve resistance to vaccines and antiviral drugs. For the last 30 years, quasispecies theory has provided a population-based framework for understanding RNA viral evolution. A quasispecies is a cloud of diverse variants that are genetically linked through mutation, interact cooperatively on a functional level, and collectively contribute to the characteristics of the population. Many predictions of quasispecies theory run counter to traditional views of microbial behavior and evolution and have profound implications for our understanding of viral disease. Here, we discuss basic principles of quasispecies theory and describe its relevance for our understanding of viral fitness, virulence, and antiviral therapeutic strategy.

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

Key Points RNA viruses have extremely high mutation rates that are orders of magnitude greater than those of DNA-based organisms. Although some of these mutations are beneficial, the vast majority are detrimental to fitness. Mutational robustness describes the preservation of phenotype in the face of ongoing mutation. Evolutionary theory suggests that high mutation rates drive the selection of mutational robustness. The relative mutational robustness of an RNA virus can be measured by experiments assessing the accumulation of mutations, the effects of random mutations or mutagen sensitivity. Factors such as a large population size and the ability to infect at high multiplicity can lead to increased robustness. In silico modelling and experimental evolution suggest that viral RNA structures are genotypically diverse but preserve a native fold. Codon usage might also confer mutational robustness at the level of the viral genome. Cellular chaperones might confer mutational robustness to RNA viruses by stabilizing mutant proteins and preventing their misfolding or aggregation. Mutational robustness might favour viral evolvability and increase the ability of a virus to survive in the dynamic host environment. Evolved robustness could complicate efforts to control viral infections through drug-induced increases in the viral mutation rate. RNA viruses have extremely high mutation rates, which are crucial for the ability of these viruses to adapt but can also lead to population extinction. Here, Andino and colleagues describe the mechanisms that RNA viruses use to cope with the high mutational load and discuss the impact of mutational robustness on population dynamics, pathogenicity and antiviral therapies. RNA viruses face dynamic environments and are masters at adaptation. During their short 'lifespans', they must surmount multiple physical, anatomical and immunological challenges. Central to their adaptative capacity is the enormous genetic diversity that characterizes RNA virus populations. Although genetic diversity increases the rate of adaptive evolution, low replication fidelity can present a risk because excess mutations can lead to population extinction. In this Review, we discuss the strategies used by RNA viruses to deal with the increased mutational load and consider how this mutational robustness might influence viral evolution and pathogenesis.

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant, BA.2.86, has emerged and spread to numerous countries worldwide, raising alarm because its spike protein contains 34 additional mutations compared with its BA.2 predecessor 1 . We examined its antigenicity using human sera and monoclonal antibodies (mAbs). Reassuringly, BA.2.86 was no more resistant to human sera than the currently dominant XBB.1.5 and EG.5.1, indicating that the new subvariant would not have a growth advantage in this regard. Importantly, sera from people who had XBB breakthrough infection exhibited robust neutralizing activity against all viruses tested, suggesting that upcoming XBB.1.5 monovalent vaccines could confer added protection. Although BA.2.86 showed greater resistance to mAbs to subdomain 1 (SD1) and receptor-binding domain (RBD) class 2 and 3 epitopes, it was more sensitive to mAbs to class 1 and 4/1 epitopes in the ‘inner face’ of the RBD that is exposed only when this domain is in the ‘up’ position. We also identified six new spike mutations that mediate antibody resistance, including E554K that threatens SD1 mAbs in clinical development. The BA.2.86 spike also had a remarkably high receptor affinity. The ultimate trajectory of this new SARS-CoV-2 variant will soon be revealed by continuing surveillance, but its worldwide spread is worrisome. A severe acute respiratory syndrome coronavirus 2 Omicron subvariant, BA.2.86, was found to be no more resistant to human sera than the currently dominant XBB.1.5 and EG.5.1, but it had a remarkably higher receptor affinity.

While influenza virus diversity and antigenic drift have been well characterized on a global scale, the factors that influence the virus' rapid evolution within and between human hosts are less clear. Given the modest effectiveness of seasonal vaccination, vaccine-induced antibody responses could serve as a potent selective pressure for novel influenza variants at the individual or community level. We used next generation sequencing of patient-derived viruses from a randomized, placebo-controlled trial of vaccine efficacy to characterize the diversity of influenza A virus and to define the impact of vaccine-induced immunity on within-host populations. Importantly, this study design allowed us to isolate the impact of vaccination while still studying natural infection. We used pre-season hemagglutination inhibition and neuraminidase inhibition titers to quantify vaccine-induced immunity directly and to assess its impact on intrahost populations. We identified 166 cases of H3N2 influenza over 3 seasons and 5119 person-years. We obtained whole genome sequence data for 119 samples and used a stringent and empirically validated analysis pipeline to identify intrahost single nucleotide variants at ≥1% frequency. Phylogenetic analysis of consensus hemagglutinin and neuraminidase sequences showed no stratification by pre-season HAI and NAI titer, respectively. In our study population, we found that the vast majority of intrahost single nucleotide variants were rare and that very few were found in more than one individual. Most samples had fewer than 15 single nucleotide variants across the entire genome, and the level of diversity did not significantly vary with day of sampling, vaccination status, or pre-season antibody titer. Contrary to what has been suggested in experimental systems, our data indicate that seasonal influenza vaccination has little impact on intrahost diversity in natural infection and that vaccine-induced immunity may be only a minor contributor to antigenic drift at local scales.

The substitution rates of transitions are higher than expected by chance relative to those of transversions. Many have argued that selection disfavors transversions, as nonsynonymous transversions are less likely to conserve biochemical properties of the original amino acid. Only recently has it become feasible to directly test this selective hypothesis by comparing the fitness effects of a large number of transition and transversion mutations. For example, a recent study of six viruses and one beta-lactamase gene did not find evidence supporting the selective hypothesis. Here, we analyze the relative fitness effects of transition and transversion mutations from our recently published genome-wide study of mutational fitness effects in influenza virus. In contrast to prior work, we find that transversions are significantly more detrimental than transitions. Using what we believe to be an improved statistical framework, we also identify a similar trend in two HIV data sets. We further demonstrate a fitness difference in transition and transversion mutations using four deep mutational scanning data sets of influenza virus and HIV, which provided adequate statistical power. We find that three of the most commonly cited radical/conservative amino acid categories are predictive of fitness, supporting their utility in studies of positive selection and codon usage bias. We conclude that selection is a major contributor to the transition:transversion substitution bias in viruses and that this effect is only partially explained by the greater likelihood of transversion mutations to cause radical as opposed to conservative amino acid changes.

Influenza remains a persistent public health challenge, because the rapid evolution of influenza viruses has led to marginal vaccine efficacy, antiviral resistance, and the annual emergence of novel strains. This evolvability is driven, in part, by the virus’s capacity to generate diversity through mutation and reassortment. Because many new traits require multiple mutations and mutations are frequently combined by reassortment, epistatic interactions between mutations play an important role in influenza virus evolution. While mutation and epistasis are fundamental to the adaptability of influenza viruses, they also constrain the evolutionary process in important ways. Here, we review recent work on mutational effects and epistasis in influenza viruses.

Mutation rates can evolve through genetic drift, indirect selection due to genetic hitchhiking, or direct selection on the physicochemical cost of high fidelity. However, for many systems, it has been difficult to disentangle the relative impact of these forces empirically. In RNA viruses, an observed correlation between mutation rate and virulence has led many to argue that their extremely high mutation rates are advantageous because they may allow for increased adaptability. This argument has profound implications because it suggests that pathogenesis in many viral infections depends on rare or de novo mutations. Here, we present data for an alternative model whereby RNA viruses evolve high mutation rates as a byproduct of selection for increased replicative speed. We find that a poliovirus antimutator, 3DG64S, has a significant replication defect and that wild-type (WT) and 3DG64S populations have similar adaptability in 2 distinct cellular environments. Experimental evolution of 3DG64S under selection for replicative speed led to reversion and compensation of the fidelity phenotype. Mice infected with 3DG64S exhibited delayed morbidity at doses well above the lethal level, consistent with attenuation by slower growth as opposed to reduced mutational supply. Furthermore, compensation of the 3DG64S growth defect restored virulence, while compensation of the fidelity phenotype did not. Our data are consistent with the kinetic proofreading model for biosynthetic reactions and suggest that speed is more important than accuracy. In contrast with what has been suggested for many RNA viruses, we find that within-host spread is associated with viral replicative speed and not standing genetic diversity.

A virus' mutational robustness is described in terms of the strength and distribution of the mutational fitness effects, or MFE. The distribution of MFE is central to many questions in evolutionary theory and is a key parameter in models of molecular evolution. Here we define the mutational fitness effects in influenza A virus by generating 128 viruses, each with a single nucleotide mutation. In contrast to mutational scanning approaches, this strategy allowed us to unambiguously assign fitness values to individual mutations. The presence of each desired mutation and the absence of additional mutations were verified by next generation sequencing of each stock. A mutation was considered lethal only after we failed to rescue virus in three independent transfections. We measured the fitness of each viable mutant relative to the wild type by quantitative RT-PCR following direct competition on A549 cells. We found that 31.6% of the mutations in the genome-wide dataset were lethal and that the lethal fraction did not differ appreciably between the HA- and NA-encoding segments and the rest of the genome. Of the viable mutants, the fitness mean and standard deviation were 0.80 and 0.22 in the genome-wide dataset and best modeled as a beta distribution. The fitness impact of mutation was marginally lower in the segments coding for HA and NA (0.88 ± 0.16) than in the other 6 segments (0.78 ± 0.24), and their respective beta distributions had slightly different shape parameters. The results for influenza A virus are remarkably similar to our own analysis of CirSeq-derived fitness values from poliovirus and previously published data from other small, single stranded DNA and RNA viruses. These data suggest that genome size, and not nucleic acid type or mode of replication, is the main determinant of viral mutational fitness effects.

  By displacing the trade-off curve along the horizontal axis by an amount equal to the rate of recovery, the R0 of any point on the trade-off curve is simply the slope of the line from the origin to the point. [...]population-level studies of chronic human immunodeficiency virus infection suggest that intermediate viral loads maximize transmission potential, reflecting a potential trade-off between the transmission and the duration of asymptomatic infection [12]. [...]the virology literature is replete with studies of interactions between virus and cell.