Explore the vast range of titles available.

A new approach to accurately determine mutation frequencies with RNA virus populations called circular sequencing (CirSeq) has been developed; a study of the genetic composition of populations of poliovirus shows the fitness landscape for each nucleotide variant in an evolving RNA virus. Evolving RNA viruses sequenced Raul Andino and colleagues report a new approach to the determination of mutation frequencies within RNA virus populations. The new technique, circular sequencing (CirSeq), uses circularized genomic RNA fragments to generate tandem repeats that then serve as substrates for next-generation sequencing. The authors use CirSeq to track the genetic composition of populations of poliovirus replicating in human cells in culture and uncover the mutational landscape of the population. The extent of change in mutation frequency for each variant over the course of passage in cell culture is a measure of the relative fitness of each variant, thereby delineating the fitness landscape for an evolving RNA virus. RNA viruses exist as genetically diverse populations 1 . It is thought that diversity and genetic structure of viral populations determine the rapid adaptation observed in RNA viruses 2 and hence their pathogenesis 3 . However, our understanding of the mechanisms underlying virus evolution has been limited by the inability to accurately describe the genetic structure of virus populations. Next-generation sequencing technologies generate data of sufficient depth to characterize virus populations, but are limited in their utility because most variants are present at very low frequencies and are thus indistinguishable from next-generation sequencing errors. Here we present an approach that reduces next-generation sequencing errors and allows the description of virus populations with unprecedented accuracy. Using this approach, we define the mutation rates of poliovirus and uncover the mutation landscape of the population. Furthermore, by monitoring changes in variant frequencies on serially passaged populations, we determined fitness values for thousands of mutations across the viral genome. Mapping of these fitness values onto three-dimensional structures of viral proteins offers a powerful approach for exploring structure–function relationships and potentially uncovering new functions. To our knowledge, our study provides the first single-nucleotide fitness landscape of an evolving RNA virus and establishes a general experimental platform for studying the genetic changes underlying the evolution of virus populations.

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.

COVID-19’s high virus transmission rates have caused a pandemic that is exacerbated by the high rates of asymptomatic and presymptomatic infections. These factors suggest that face masks and social distance could be paramount in containing the pandemic. We examined the efficacy of each measure and the combination of both measures using an agent-based model within a closed space that approximated real-life interactions. By explicitly considering different fractions of asymptomatic individuals, as well as a realistic hypothesis of face masks protection during inhaling and exhaling, our simulations demonstrate that a synergistic use of face masks and social distancing is the most effective intervention to curb the infection spread. To control the pandemic, our models suggest that high adherence to social distance is necessary to curb the spread of the disease, and that wearing face masks provides optimal protection even if only a small portion of the population comply with social distance. Finally, the face mask effectiveness in curbing the viral spread is not reduced if a large fraction of population is asymptomatic. Our findings have important implications for policies that dictate the reopening of social gatherings.

NGS error rates are very low in libraries prepared by CirSeq, allowing ultra-rare genetic variant detection in populations. Sequencing errors are easily identified as replicates of a particular sequence are physically linked during amplification. Circular resequencing (CirSeq) is a novel technique for efficient and highly accurate next-generation sequencing (NGS) of RNA virus populations. The foundation of this approach is the circularization of fragmented viral RNAs, which are then redundantly encoded into tandem repeats by 'rolling-circle' reverse transcription. When sequenced, the redundant copies within each read are aligned to derive a consensus sequence of their initial RNA template. This process yields sequencing data with error rates far below the variant frequencies observed for RNA viruses, facilitating ultra-rare variant detection and accurate measurement of low-frequency variants. Although library preparation takes ∼5 d, the high-quality data generated by CirSeq simplifies downstream data analysis, making this approach substantially more tractable for experimentalists.

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.

Aedes aegypti transmit pathogenic arboviruses while the mosquito itself tolerates the infection. We examine a piRNA-based immunity that relies on the acquisition of viral derived cDNA (vDNA) and how this pathway discriminates between self and non-self. The piRNAs derived from these vDNAs are essential for virus control and Piwi4 has a central role in the pathway. Piwi4 binds preferentially to virus-derived piRNAs but not to transposon-targeting piRNAs. Analysis of episomal vDNA from infected cells reveals that vDNA molecules are acquired through a discriminatory process of reverse-transcription and recombination directed by endogenous retrotransposons. Using a high-resolution Ae. aegypti genomic sequence, we found that vDNAs integrated in the host genome as endogenous viral elements (EVEs), produce antisense piRNAs that are preferentially loaded onto Piwi4. Importantly, EVE-derived piRNAs are specifically loaded onto Piwi4 to inhibit virus replication. Thus, Ae. aegypti employs a sophisticated antiviral mechanism that promotes viral persistence and generates long-lasting adaptive immunity.

Dengue virus (DENV) cycles between mosquito and mammalian hosts. To examine how DENV populations adapt to these different host environments, we used serial passage in human and mosquito cell lines and estimated fitness effects for all single-nucleotide variants in these populations using ultra-deep sequencing. This allowed us to determine the contributions of beneficial and deleterious mutations to the collective fitness of the population. Our analysis revealed that the continuous influx of a large burden of deleterious mutations counterbalances the effect of rare, host-specific beneficial mutations to shape the path of adaptation. Beneficial mutations preferentially map to intrinsically disordered domains in the viral proteome and cluster to defined regions in the genome. These phenotypically redundant adaptive alleles may facilitate host-specific DENV adaptation. Importantly, the evolutionary constraints described in our simple system mirror trends observed across DENV and Zika strains, indicating it recapitulates key biophysical and biological constraints shaping long-term viral evolution. Viruses are constantly evolving as a result of mutations in their genetic material and environmental pressures. Viruses switching between insects and mammals face unique evolutionary pressures because they must retain their ability to infect both types of organisms. Yet, the mutations in a virus that may be beneficial in an insect may be different from the ones that may be beneficial in a mammal. Mutations in one host may be even harmful in the other. To learn more about how such viruses thrive as they switch between hosts, Dolan, Taguwa et al. studied the dengue virus, which causes over 390 million infections and over 10,000 deaths each year around the globe. They compared the mutations that occurred as the virus multiplied in human and mosquito cells grown in a laboratory. In the experiments, they used a method called ultra-deep RNA sequencing to identify every change that occurred in the genetic material of the virus each time it multiplied. They determined whether the mutations were beneficial or harmful based on whether they became more common – suggesting they helped the virus survive – or whether they did not persist because they were likely harmful or even fatal to the virus. The experiments showed that many harmful mutations constantly occur in the virus, in both human and mosquito cells. Beneficial changes happen rarely, and those that do are usually only helpful in one type of cell. Fatal mutations tended to occur in parts of the genetic material that encodes regions in the viral proteins that must remain the same. These structural elements appear to be essential to the virus’s survival and unable to undergo change, which makes them good targets for antiviral drugs or vaccines. The techniques used in the study may be useful for investigating other viruses and for understanding the evolutionary constraints on viruses more generally. This may help scientists develop antiviral drugs or vaccines that will remain effective even as viruses continue to evolve and mutate.

Honey bees are essential pollinators of numerous agricultural crops. Since 2006, honey bee populations have suffered considerable annual losses that are partially attributed to Colony Collapse Disorder (CCD). CCD is an unexplained phenomenon that correlates with elevated incidence of pathogens, including RNA viruses. Honey bees are eusocial insects that live in colonies of genetically related individuals that work in concert to gather and store nutrients. Their social organization provides numerous benefits, but also facilitates pathogen transmission between individuals. To investigate honey bee antiviral defense mechanisms, we developed an RNA virus infection model and discovered that administration of dsRNA, regardless of sequence, reduced virus infection. Our results suggest that dsRNA, a viral pathogen associated molecular pattern (PAMP), triggers an antiviral response that controls virus infection in honey bees.

Acquisition of mutations is central to evolution; however, the detrimental effects of most mutations on protein folding and stability limit protein evolvability. Molecular chaperones, which suppress aggregation and facilitate polypeptide folding, may alleviate the effects of destabilizing mutations thus promoting sequence diversification. To illuminate how chaperones can influence protein evolution, we examined the effect of reduced activity of the chaperone Hsp90 on poliovirus evolution. We find that Hsp90 offsets evolutionary trade-offs between protein stability and aggregation. Lower chaperone levels favor variants of reduced hydrophobicity and protein aggregation propensity but at a cost to protein stability. Notably, reducing Hsp90 activity also promotes clusters of codon-deoptimized synonymous mutations at inter-domain boundaries, likely to facilitate cotranslational domain folding. Our results reveal how a chaperone can shape the sequence landscape at both the protein and RNA levels to harmonize competing constraints posed by protein stability, aggregation propensity, and translation rate on successful protein biogenesis. It remains poorly understood whether and how chaperones control protein evolution. Here the authors show how the chaperone Hsp90 shapes the sequence space of its client, poliovirus protein P1, at the polypeptide and RNA level to balance the evolutionary trade-offs between protein stability, aggregation and translation rate.

The impact of vaccination on SARS-CoV-2 infectiousness is not well understood. We compared longitudinal viral shedding dynamics in unvaccinated and fully vaccinated adults. SARS-CoV-2-infected adults were enrolled within 5 days of symptom onset and nasal specimens were self-collected daily for two weeks and intermittently for an additional two weeks. SARS-CoV-2 RNA load and infectious virus were analyzed relative to symptom onset stratified by vaccination status. We tested 1080 nasal specimens from 52 unvaccinated adults enrolled in the pre-Delta period and 32 fully vaccinated adults with predominantly Delta infections. While we observed no differences by vaccination status in maximum RNA levels, maximum infectious titers and the median duration of viral RNA shedding, the rate of decay from the maximum RNA load was faster among vaccinated; maximum infectious titers and maximum RNA levels were highly correlated. Furthermore, amongst participants with infectious virus, median duration of infectious virus detection was reduced from 7.5 days (IQR: 6.0–9.0) in unvaccinated participants to 6 days (IQR: 5.0–8.0) in those vaccinated (P = 0.02). Accordingly, the odds of shedding infectious virus from days 6 to 12 post-onset were lower among vaccinated participants than unvaccinated participants (OR 0.42 95% CI 0.19–0.89). These results indicate that vaccination had reduced the probability of shedding infectious virus after 5 days from symptom onset.