Luria-delbruck estimation of turnip mosaic virus mutation rate in vivo

Single-cell mutation rate of turnip crinkle virus (-)-strand replication intermediates

Viruses with single-stranded, positive-sense (+) RNA genomes incur high numbers of errors during replication, thereby creating diversified genome populations from which new, better adapted viral variants can emerge. However, a definitive error rate is known for a relatively few (+) RNA plant viruses, due to challenges to account for perturbations caused by natural selection and/or experimental set-ups. To address these challenges, we developed a new approach that exclusively profiled errors in the (-)-strand replication intermediates of turnip crinkle virus (TCV), in singly infected cells. A series of controls and safeguards were devised to ensure errors inherent to the experimental process were accounted for. This approach permitted the estimation of a TCV error rate of 8.47 X 10-5 substitution per nucleotide site per cell infection. Importantly, the characteristic error distribution pattern among the 50 copies of 2,363-base-pair cDNA fragments predicted that nearly all TCV (-) strands were products of one replication cycle per cell. Furthermore, some of the errors probably elevated error frequencies by lowering the fidelity of TCV RNA-dependent RNA polymerase, and/or permitting occasional re-replication of progeny genomes. In summary, by profiling errors in TCV (-)-strand intermediates incurred during replication in single cells, this study provided strong support for a stamping machine mode of replication employed by a (+) RNA virus.

Impact of genetic drift, selection and accumulation level on virus adaptation to its host plants

The efficiency of plant major resistance genes is limited by the emergence and spread of resistance-breaking mutants. Modulation of the evolutionary forces acting on pathogen populations constitutes a promising way to increase the durability of these genes. We studied the effect of four plant traits affecting these evolutionary forces on the rate of resistance breakdown (RB) by a virus. Two of these traits correspond to virus effective population sizes (N_e ) at either plant inoculation or during infection. The third trait corresponds to differential selection exerted by the plant on the virus population. Finally, the fourth trait corresponds to within-plant virus accumulation (VA). These traits were measured experimentally on Potato virus Y (PVY) inoculated to a set of 84 pepper doubled-haploid lines, all carrying the same pvr2³ resistance gene, but having contrasting genetic backgrounds. The lines showed extensive variation for the rate of pvr2³ RB by PVY and for the four other traits of interest. A generalized linear model showed that three of these four traits, with the exception of N_e at inoculation, and several pairwise interactions between them had significant effects on RB. RB increased with increasing values of N_e during plant infection or VA. The effect of differential selection was more complex because of a strong interaction with VA. When VA was high, RB increased as the differential selection increased. An opposite relationship between RB and differential selection was observed when VA was low. This study provides a framework to select plants with appropriate virus evolution-related traits to avoid or delay RB.

Tobamoviruses as Models for the Study of Virus Evolution

The study of tobacco mosaic virus and other tobamovirus species has greatly contributed to the development of all areas of virology, including virus evolution. Research with tobamoviruses has been pioneer, or particularly significant, in all major areas of research in this field, including: the characterization of the genetic diversity of virus populations, the mechanisms and rates of generation of genetic diversity, the analysis of the genetic structure of virus populations and of the factors that shape it, the adaptation of viruses to hosts and the evolution of host range, and the evolution of virus taxa and of virus-host interactions. Many of these continue to be hot topics in evolutionary biology, or have been identified recently as such, including (i) host-range evolution, (ii) predicting the overcoming of resistance in crops, (iii) trade-offs between virus life-history traits in virus evolution, and (iv) the codivergence of viruses and hosts at different taxonomical and spatial scales. Tobamoviruses may be particularly appropriate to address these topics with plant viruses, as they provide convenient experimental systems, and as the detailed knowledge on their molecular and structural biology allows the analysis of the mechanisms behind evolutionary processes. Also, the extensive information on parameters related to infection dynamics and population structure may facilitate the development of realistic models to predict virus evolution. Certainly, tobamoviruses will continue to be favorite system for the study of virus evolution.

Evolution and emergence of plant viruses

Viruses are common agents of plant infectious diseases. During last decades, worldwide agriculture production has been compromised by a series of epidemics caused by new viruses that spilled over from reservoir species or by new variants of classic viruses that show new pathogenic and epidemiological properties. Virus emergence has been generally associated with ecological change or with intensive agronomical practices. However, the complete picture is much more complex since the viral populations constantly evolve and adapt to their new hosts and vectors. This chapter puts emergence of plant viruses into the framework of evolutionary ecology, genetics, and epidemiology. We will stress that viral emergence begins with the stochastic transmission of preexisting genetic variants from the reservoir to the new host, whose fate depends on their fitness on each hosts, followed by adaptation to new hosts or vectors, and finalizes with an efficient epidemiological spread.

Unbiased estimation of mutation rates under fluctuating final counts

Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known. In both cases, unbiased estimation methods are proposed. Their statistical properties are assessed both theoretically and through Monte-Carlo simulation. As an application, the data from two well known fluctuation analysis studies on Mycobacterium tuberculosis are reexamined.

Variability in the mutation rates of RNA viruses

ABSTRACT: 

It is well established that RNA viruses show extremely high mutation rates, but less attention has been paid to the fact that their mutation rates also vary strongly, from 10-6 to 10-4 substitutions per nucleotide per cell infection. The causes explaining this variability are still poorly understood, but candidate factors are the viral genome size and polarity, host-specific gene expression patterns, or the intracellular environment. Differences between animal and plant viruses, or between arthropod-borne and directly transmitted viruses have also been postulated. Finally, RNA viruses may be able to regulate the rate at which new mutations spread in the population by modifying features of the viral infection cycle, such as lysis time.

Variation in RNA virus mutation rates across host cells

It is well established that RNA viruses exhibit higher rates of spontaneous mutation than DNA viruses and microorganisms. However, their mutation rates vary amply, from 10⁻⁶ to 10⁻⁴ substitutions per nucleotide per round of copying (s/n/r) and the causes of this variability remain poorly understood. In addition to differences in intrinsic fidelity or error correction capability, viral mutation rates may be dependent on host factors. Here, we assessed the effect of the cellular environment on the rate of spontaneous mutation of the vesicular stomatitis virus (VSV), which has a broad host range and cell tropism. Luria-Delbrück fluctuation tests and sequencing showed that VSV mutated similarly in baby hamster kidney, murine embryonic fibroblasts, colon cancer, and neuroblastoma cells (approx. 10⁻⁵ s/n/r). Cell immortalization through p53 inactivation and oxygen levels (1–21%) did not have a significant impact on viral replication fidelity. This shows that previously published mutation rates can be considered reliable despite being based on a narrow and artificial set of laboratory conditions. Interestingly, we also found that VSV mutated approximately four times more slowly in various insect cells compared with mammalian cells. This may contribute to explaining the relatively slow evolution of VSV and other arthropod-borne viruses in nature.

RNA viruses show high rates of spontaneous mutation, a feature that profoundly influences viral evolution, disease emergence, the appearance of drug resistances, and vaccine efficacy. However, RNA virus mutation rates vary substantially and the factors determining this variability remain poorly understood. Here, we investigated the effects of host factors on viral replication fidelity by measuring the viral mutation rate in different cell types and under various culturing conditions. To carry out these experiments we chose the vesicular stomatitis virus (VSV), an insect-transmitted mammalian RNA virus with an extremely wide cellular and host tropism. We found that the VSV replication machinery was robust to changes in cellular physiology driven by cell immortalization or shifts in temperature and oxygen levels. In contrast, VSV mutated significantly more slowly in insect cells than in mammalian cells, a finding may help us to understand why arthropod-borne viruses tend to evolve more slowly than directly transmitted viruses in nature.

Correlation between mutation rate and genome size in riboviruses: mutation rate of bacteriophage Qβ

Genome sizes and mutation rates covary across all domains of life. In unicellular organisms and DNA viruses, they show an inverse relationship known as Drake’s rule. However, it is still unclear whether a similar relationship exists between genome sizes and mutation rates in RNA genomes. Coronaviruses, the RNA viruses with the largest genomes (∼30 kb), encode a proofreading 3′ exonuclease that allows them to increase replication fidelity. However, it is unknown whether, conversely, the RNA viruses with the smallest genomes tend to show particularly high mutation rates. To test this, we measured the mutation rate of bacteriophage Qβ, a 4.2-kb levivirus. Amber reversion-based Luria–Delbrück fluctuation tests combined with mutant sequencing gave an estimate of 1.4 × 10⁻⁴ substitutions per nucleotide per round of copying, the highest mutation rate reported for any virus using this method. This estimate was confirmed using a direct plaque sequencing approach and after reanalysis of previously published estimates for this phage. Comparison with other riboviruses (all RNA viruses except retroviruses) provided statistical support for a negative correlation between mutation rates and genome sizes. We suggest that the mutation rates of RNA viruses might be optimized for maximal adaptability and that the value of this optimum may in turn depend inversely on genome size.

Improving the effectiveness of artificial microRNA (amiR)-mediated resistance against Turnip mosaic virus by combining two amiRs or by targeting highly conserved viral genomic regions

A drawback of recent antiviral therapies based on the transgenic expression of artificial microRNAs (amiRs) is the ease with which viruses generate escape mutations. Here, we show two alternative strategies for improving the effectiveness of resistance in plants. First, we expressed two amiRs complementary to independent targets in the viral genome, and second, we designed amiRs complementary to highly conserved RNA motifs in the viral genome.

Ultradeep sequencing analysis of population dynamics of virus escape mutants in RNAi-mediated resistant plants

Plant artificial micro-RNAs (amiRs) have been engineered to target viral genomes and induce their degradation. However, the exceptional evolutionary plasticity of RNA viruses threatens the durability of the resistance conferred by these amiRs. It has recently been shown that viral populations not experiencing strong selective pressure from an antiviral amiR may already contain enough genetic variability in the target sequence to escape plant resistance in an almost deterministic manner. Furthermore, it has also been shown that viral populations exposed to subinhibitory concentrations of the antiviral amiR speed up this process. In this article, we have characterized the molecular evolutionary dynamics of an amiR target sequence in a viral genome under both conditions. The use of Illumina ultradeep sequencing has allowed us to identify virus sequence variants at frequencies as low as 2 × 10(-6) and to track their variation in time before and after the viral population was able of successfully infecting plants fully resistant to the ancestral virus. We found that every site in the amiR-target sequence of the viral genome presented variation and that the variant that eventually broke resistance was sampled among the many coexisting ones. In this system, viral evolution in fully susceptible plants results from an equilibrium between mutation and genetic drift, whereas evolution in partially resistant plants originates from more complex dynamics involving mutation, selection, and drift.