Correction: Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.

[This corrects the article DOI: 10.1371/journal.pcbi.1006085.].

Role of Acrostyle Cuticular Proteins in the Retention of an Aphid Salivary Effector.

To avoid the activation of plant defenses and ensure sustained feeding, aphids are assumed to use their mouthparts to deliver effectors into plant cells. A recent study has shown that effectors detected near feeding sites are differentially distributed in plant tissues. However, the precise process of effector delivery into specific plant compartments is unknown. The acrostyle, a cuticular organ located at the tip of maxillary stylets that transiently binds plant viruses via its stylin proteins, may participate in this specific delivery process. Here, we demonstrate that Mp10, a saliva effector released into the plant cytoplasm during aphid probing, binds to the acrostyles of Acyrthosiphon pisum and Myzus persicae. The effector probably interacts with Stylin-03 as a lowered Mp10-binding to the acrostyle was observed upon RNAi-mediated reduction in Stylin-03 production. In addition, Stylin-03 and Stylin-01 RNAi aphids exhibited changes in their feeding behavior as evidenced by electrical penetration graph experiments showing longer aphid probing behaviors associated with watery saliva release into the cytoplasm of plant cells. Taken together, these data demonstrate that the acrostyle also has effector binding capacity and supports its role in the delivery of aphid effectors into plant cells.

Turnip Mosaic Virus Is a Second Example of a Virus Using Transmission Activation for Plant-to-Plant Propagation by Aphids.

Cauliflower mosaic virus (CaMV; family Caulimoviridae) responds to the presence of aphid vectors on infected plants by forming specific transmission morphs. This phenomenon, coined transmission activation (TA), controls plant-to-plant propagation of CaMV. A fundamental question is whether other viruses rely on TA. Here, we demonstrate that transmission of the unrelated turnip mosaic virus (TuMV; family Potyviridae) is activated by the reactive oxygen species H2O2 and inhibited by the calcium channel blocker LaCl3 H2O2-triggered TA manifested itself by the induction of intermolecular cysteine bonds between viral helper component protease (HC-Pro) molecules and by the formation of viral transmission complexes, composed of TuMV particles and HC-Pro that mediates vector binding. Consistently, LaCl3 inhibited intermolecular HC-Pro cysteine bonds and HC-Pro interaction with viral particles. These results show that TuMV is a second virus using TA for transmission but using an entirely different mechanism than CaMV. We propose that TuMV TA requires reactive oxygen species (ROS) and calcium signaling and that it is operated by a redox switch.IMPORTANCE Transmission activation, i.e., a viral response to the presence of vectors on infected hosts that regulates virus acquisition and thus transmission, is an only recently described phenomenon. It implies that viruses contribute actively to their transmission, something that has been shown before for many other pathogens but not for viruses. However, transmission activation has been described so far for only one virus, and it was unknown whether other viruses also rely on transmission activation. Here we present evidence that a second virus uses transmission activation, suggesting that it is a general transmission strategy.

Small Bottleneck Size in a Highly Multipartite Virus during a Complete Infection Cycle.

Multipartite viruses package their genomic segments independently and thus incur the risk of being unable to transmit their entire genome during host-to-host transmission if they undergo severe bottlenecks. In this paper, we estimated the bottleneck size during one infection cycle of Faba bean necrotic stunt virus (FBNSV), an octopartite nanovirus whose segments have been previously shown to converge to particular and unequal relative frequencies within host plants and aphid vectors. Two methods were used to derive this estimate, one based on the probability of transmission of the virus and the other based on the temporal evolution of the relative frequency of markers for two genomic segments, one frequent and one rare (segment N and S, respectively), both in plants and vectors. Our results show that FBNSV undergoes severe bottlenecks during aphid transmission. Further, even though the bottlenecks are always narrow under our experimental conditions, they slightly widen with the number of transmitting aphids. In particular, when several aphids are used for transmission, the bottleneck size of the segments is also affected by within-plant processes and, importantly, significantly differs across segments. These results indicate that genetic drift not only must be an important process affecting the evolution of these viruses but also that these effects vary across genomic segments and, thus, across viral genes, a rather unique and intriguing situation. We further discuss the potential consequences of our findings for the transmission of multipartite viruses.IMPORTANCE Multipartite viruses package their genomic segments in independent capsids. The most obvious cost of such genomic structure is the risk of losing at least one segment during host-to-host transmission. A theoretical study has shown that for nanoviruses, composed of 6 to 8 segments, hundreds of copies of each segment need to be transmitted to ensure that at least one copy of each segment was present in the host. These estimations seem to be very high compared to the size of the bottlenecks measured with other viruses. Here, we estimated the bottleneck size during one infection cycle of FBNSV, an octopartite nanovirus. We show that these bottlenecks are always narrow (few viral particles) and slightly widen with the number of transmitting aphids. These results contrast with theoretical predictions and illustrate the fact that a new conceptual framework is probably needed to understand the transmission of highly multipartite viruses.

Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.

Analyzing the Influence of Landscape Aggregation on Disease Spread to Improve Management Strategies.

Epidemiological models are increasingly used to predict epidemics and improve management strategies. However, they rarely consider landscape characteristics although such characteristics can influence the epidemic dynamics and, thus, the effectiveness of disease management strategies. Here, we present a generic in silico approach which assesses the influence of landscape aggregation on the costs associated with an epidemic and on improved management strategies. We apply this approach to sharka, one of the most damaging diseases of Prunus trees, for which a management strategy is already applied in France. Epidemic simulations were carried out with a spatiotemporal stochastic model under various management strategies in landscapes differing in patch aggregation. Using sensitivity analyses, we highlight the impact of management parameters on the economic output of the model. We also show that the sensitivity analysis can be exploited to identify several strategies that are, according to the model, more profitable than the current French strategy. Some of these strategies are specific to a given aggregation level, which shows that management strategies should generally be tailored to each specific landscape. However, we also identified a strategy that is efficient for all levels of landscape aggregation. This one-size-fits-all strategy has important practical implications because of its simple applicability at a large scale.

Improving Management Strategies of Plant Diseases Using Sequential Sensitivity Analyses.

Improvement of management strategies of epidemics is often hampered by constraints on experiments at large spatiotemporal scales. A promising approach consists of modeling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimization of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach (i.e., a practical improvement method approximating an optimal solution) based on sequential sensitivity analyses. In addition, we use an economic improvement criterion based on the net present value, accounting for both the cost of the different control measures and the benefit generated by disease suppression. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach, and plum), the management of which in orchards is mainly based on surveillance and tree removal. We identified the key parameters of a spatiotemporal model simulating sharka spread and control and approximated optimal values for these parameters. The results indicate that the current French management of sharka efficiently controls the disease, but it can be economically improved using alternative strategies that are identified and discussed. The general approach should help policy makers to design sustainable and cost-effective strategies for disease management.

Demographics of natural oral infection of mosquitos by Venezuelan equine encephalitis virus.

The within-host diversity of virus populations can be drastically limited during between-host transmission, with primary infection of hosts representing a major constraint to diversity maintenance. However, there is an extreme paucity of quantitative data on the demographic changes experienced by virus populations during primary infection. Here, the multiplicity of cellular infection (MOI) and population bottlenecks were quantified during primary mosquito infection by Venezuelan equine encephalitis virus, an arbovirus causing neurological disease in humans and equids.

Assessing the Mismatch Between Incubation and Latent Periods for Vector-Borne Diseases: The Case of Sharka.

The relative durations of the incubation period (the time between inoculation and symptom expression) and of the latent period (the time between inoculation and infectiousness of the host) are poorly documented for plant diseases. However, the extent of asynchrony between the ends of these two periods (i.e., their mismatch) can be a key determinant of the epidemic dynamics for many diseases and consequently it is of primary interest in the design of disease management strategies. In order to assess this mismatch, an experimental approach was developed and applied using sharka, a severe disease caused by Plum pox virus (PPV, genus Potyvirus, family Potyviridae) affecting trees belonging to the genus Prunus. Leaves of infected young peach trees were used individually as viral sources in aphid-mediated transmission tests carried out at different time points postinoculation in order to bracket symptom onset. By fitting a nonlinear logistic model to the obtained transmission rates, we demonstrated that the first symptoms appear on leaves 1 day before they rapidly become infectious. In addition, among symptomatic leaves, symptom intensity and transmission rate are positively correlated. These results strengthen the conclusion that, under our experimental conditions, incubation and latent periods of PPV infection are almost synchronous.

Frequency-dependent assistance as a way out of competitive exclusion between two strains of an emerging virus.

Biological invasions are the main causes of emerging viral diseases and they favour the co-occurrence of multiple species or strains in the same environment. Depending on the nature of the interaction, co-occurrence can lead to competitive exclusion or coexistence. The successive fortuitous introductions of two strains of Tomato yellow leaf curl virus (TYLCV-Mld and TYLCV-IL) in Réunion Island provided an ideal opportunity to study the invasion of, and competition between, these worldwide emerging pathogens. During a 7-year field survey, we observed a displacement of the resident TYLCV-Mld by the newcomer TYLCV-IL, with TYLCV-Mld remaining mostly in co-infected plants. To understand the factors associated with this partial displacement, biological traits related to fitness were measured. The better ecological aptitude of TYLCV-IL in single infections was demonstrated, which explains its rapid spread. However, we demonstrate that the relative fitness of virus strains can drastically change between single infections and co-infections. An epidemiological model parametrized with our experimental data predicts that the two strains will coexist in the long run through assistance by the fitter strain. This rare case of unilateral facilitation between two pathogens leads to frequency-dependent selection and maintenance of the less fit strain.

Distribution of the phenotypic effects of random homologous recombination between two virus species.

Recombination has an evident impact on virus evolution and emergence of new pathotypes, and has generated an immense literature. However, the distribution of phenotypic effects caused by genome-wide random homologous recombination has never been formally investigated. Previous data on the subject have promoted the implicit view that most viral recombinant genomes are likely to be deleterious or lethal if the nucleotide identity of parental sequences is below 90%. We decided to challenge this view by creating a bank of near-random recombinants between two viral species of the genus Begomovirus (Family Geminiviridae) exhibiting 82% nucleotide identity, and by testing infectivity and in planta accumulation of recombinant clones randomly extracted from this bank. The bank was created by DNA-shuffling-a technology initially applied to the random shuffling of individual genes, and here implemented for the first time to shuffle full-length viral genomes. Together with our previously described system allowing the direct cloning of full-length infectious geminivirus genomes, it provided a unique opportunity to generate hundreds of "mosaic" virus genomes, directly testable for infectivity. A subset of 47 randomly chosen recombinants was sequenced, individually inoculated into tomato plants, and compared with the parental viruses. Surprisingly, our results showed that all recombinants were infectious and accumulated at levels comparable or intermediate to that of the parental clones. This indicates that, in our experimental system, despite the fact that the parental genomes differ by nearly 20%, lethal and/or large deleterious effects of recombination are very rare, in striking contrast to the common view that has emerged from previous studies published on other viruses.

A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data.

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available.

Dynamics of the rice yellow mottle disease in western Burkina Faso: Epidemic monitoring, spatio-temporal variation of viral diversity, and pathogenicity in a disease hotspot.

The rice yellow mottle virus (RYMV) is a model in plant virus molecular epidemiology, with the reconstruction of historical introduction routes at the scale of the African continent. However, information on patterns of viral prevalence and viral diversity over multiple years at a local scale remains scarce, in spite of potential implications for crop protection. Here, we describe a 5-year (2015-9) monitoring of RYMV prevalence in six sites from western Burkina Faso (geographic areas of Bama, Banzon, and Karfiguela). It confirmed one irrigated site as a disease hotspot and also found one rainfed lowland (RL) site with occasional high prevalence levels. Within the studied fields, a pattern of disease aggregation was evidenced at a 5-m distance, as expected for a mechanically transmitted virus. Next, we monitored RYMV genetic diversity in the irrigated disease hotspot site, revealing a high viral diversity, with the current coexistence of various distinct genetic groups at the site scale (ca. 520 ha) and also within various specific fields (25 m side). One genetic lineage, named S1bzn, is the most recently emerged group and increased in frequency over the studied period (from 20 per cent or less in 2015-6 to more than 65 per cent in 2019). Its genome results from a recombination between two other lineages (S1wa and S1ca). Finally, experimental work revealed that three rice varieties commonly cultivated in Burkina Faso were not different in terms of resistance level, and we also found no significant effect of RYMV genetic groups on symptom expression and viral load. We found, however, that infection outcome depended on the specific RYMV isolate, with two isolates from the lineage S1bzn accumulating at the highest level at early infections. Overall, this study documents a case of high viral prevalence, high viral diversity, and co-occurrence of divergent genetic lineages at a small geographic scale. A recently emerged lineage, which comprises viral isolates inducing severe symptoms and high accumulation under controlled conditions, could be recently rising through natural selection. Following up the monitoring of RYMV diversity is required to confirm this trend and further understand the factors driving the local maintenance of viral diversity.

Beyond the consensus: dissecting within-host viral population diversity of foot-and-mouth disease virus by using next-generation genome sequencing.

The diverse sequences of viral populations within individual hosts are the starting material for selection and subsequent evolution of RNA viruses such as foot-and-mouth disease virus (FMDV). Using next-generation sequencing (NGS) performed on a Genome Analyzer platform (Illumina), this study compared the viral populations within two bovine epithelial samples (foot lesions) from a single animal with the inoculum used to initiate experimental infection. Genomic sequences were determined in duplicate sequencing runs, and the consensus sequence of the inoculum determined by NGS was identical to that previously determined using the Sanger method. However, NGS revealed the fine polymorphic substructure of the viral population, from nucleotide variants present at just below 50% frequency to those present at fractions of 1%. Some of the higher-frequency polymorphisms identified encoded changes within codons associated with heparan sulfate binding and were present in both foot lesions, revealing intermediate stages in the evolution of a tissue culture-adapted virus replicating within a mammalian host. We identified 2,622, 1,434, and 1,703 polymorphisms in the inoculum and in the two foot lesions, respectively: most of the substitutions occurred in only a small fraction of the population and represented the progeny from recent cellular replication prior to onset of any selective pressures. We estimated the upper limit for the genome-wide mutation rate of the virus within a cell to be 7.8 × 10(-4) per nucleotide. The greater depth of detection achieved by NGS demonstrates that this method is a powerful and valuable tool for the dissection of FMDV populations within hosts.

Dynamics of the multiplicity of cellular infection in a plant virus.

Recombination, complementation and competition profoundly influence virus evolution and epidemiology. Since viruses are intracellular parasites, the basic parameter determining the potential for such interactions is the multiplicity of cellular infection (cellular MOI), i.e. the number of viral genome units that effectively infect a cell. The cellular MOI values that prevail in host organisms have rarely been investigated, and whether they remain constant or change widely during host invasion is totally unknown. Here, we fill this experimental gap by presenting the first detailed analysis of the dynamics of the cellular MOI during colonization of a host plant by a virus. Our results reveal ample variations between different leaf levels during the course of infection, with values starting close to 2 and increasing up to 13 before decreasing to initial levels in the latest infection stages. By revealing wide dynamic changes throughout a single infection, we here illustrate the existence of complex scenarios where the opportunity for recombination, complementation and competition among viral genomes changes greatly at different infection phases and at different locations within a multi-cellular host.

Characterizing viral within-host diversity in fast and non-equilibrium demo-genetic dynamics.

High-throughput sequencing has opened the route for a deep assessment of within-host genetic diversity that can be used, e.g., to characterize microbial communities and to infer transmission links in infectious disease outbreaks. The performance of such characterizations and inferences cannot be analytically assessed in general and are often grounded on computer-intensive evaluations. Then, being able to simulate within-host genetic diversity across time under various demo-genetic assumptions is paramount to assess the performance of the approaches of interest. In this context, we built an original model that can be simulated to investigate the temporal evolution of genotypes and their frequencies under various demo-genetic assumptions. The model describes the growth and the mutation of genotypes at the nucleotide resolution conditional on an overall within-host viral kinetics, and can be tuned to generate fast non-equilibrium demo-genetic dynamics. We ran simulations of this model and computed classic diversity indices to characterize the temporal variation of within-host genetic diversity (from high-throughput amplicon sequences) of virus populations under three demographic kinetic models of viral infection. Our results highlight how demographic (viral load) and genetic (mutation, selection, or drift) factors drive variations in within-host diversity during the course of an infection. In particular, we observed a non-monotonic relationship between pathogen population size and genetic diversity, and a reduction of the impact of mutation on diversity when a non-specific host immune response is activated. The large variation in the diversity patterns generated in our simulations suggests that the underlying model provides a flexible basis to produce very diverse demo-genetic scenarios and test, for instance, methods for the inference of transmission links during outbreaks.

Synergy between an emerging monopartite begomovirus and a DNA-B component.

In recent decades, a legion of monopartite begomoviruses transmitted by the whitefly Bemisia tabaci has emerged as serious threats to vegetable crops in Africa. Recent studies in Burkina Faso (West Africa) reported the predominance of pepper yellow vein Mali virus (PepYVMLV) and its frequent association with a previously unknown DNA-B component. To understand the role of this DNA-B component in the emergence of PepYVMLV, we assessed biological traits related to virulence, virus accumulation, location in the tissue and transmission. We demonstrate that the DNA-B component is not required for systemic movement and symptom development of PepYVMLV (non-strict association), but that its association produces more severe symptoms including growth arrest and plant death. The increased virulence is associated with a higher viral DNA accumulation in plant tissues, an increase in the number of contaminated nuclei of the phloem parenchyma and in the transmission rate by B. tabaci. Our results suggest that the association of a DNA-B component with the otherwise monopartite PepYVMLV is a key factor of its emergence.

The relationship between mutation frequency and replication strategy in positive-sense single-stranded RNA viruses.

For positive-sense single-stranded RNA virus genomes, there is a trade-off between the mutually exclusive tasks of transcription, translation and encapsidation. The replication strategy that maximizes the intracellular growth rate of the virus requires iterative genome transcription from positive to negative, and back to positive sense. However, RNA viruses experience high mutation rates, and the proportion of genomes with lethal mutations increases with the number of replication cycles. Thus, intracellular mutant frequency will depend on the replication strategy. Introducing apparently realistic mutation rates into a model of viral replication demonstrates that strategies that maximize viral growth rate could result in an average of 26 mutations per genome by the time plausible numbers of positive strands have been generated, and that virus viability could be as low as 0.1 per cent. At high mutation rates or when a high proportion of mutations are deleterious, the optimal strategy shifts towards synthesizing more negative strands per positive strand, and in extremis towards a 'stamping-machine' replication mode where all the encapsidated genomes come from only two transcriptional steps. We conclude that if viral mutation rates are as high as current estimates suggest, either mutation frequency must be considerably higher than generally anticipated and the proportion of viable viruses produced extremely small, or replication strategies cannot be optimized to maximize viral growth rate. Mechanistic models linking mutation frequency to replication mechanisms coupled with data generated through new deep-sequencing technologies could play an important role in improving the estimates of viral mutation rate.

Management of yellow dwarf disease in Europe in a post-neonicotinoid agriculture.

Barley/cereal yellow dwarf viruses (YDVs) cause yellow dwarf disease (YDD), which is a continuous risk to cereals production worldwide. These viruses cause leaf yellowing and stunting, resulting in yield reductions of up to 80%. YDVs have been a consistent but low-level problem in European cereal cultivation for the last three decades, mostly due to the availability of several effective insecticides (largely pyrethroids and more recently neonicotinoids) against aphid vectors. However, this has changed recently, with many insecticides being lost, culminating in a recent European Union (EU) regulation prohibiting outdoor use of the neonicotinoid-insecticide compounds. This change is coupled with the growing challenge of insecticide-resistant aphids, the lack of genetic resources against YDVs, and a knowledge deficit around the parameters responsible for the emergence and spread of YDD. This means that economic sustainability of cereal cultivation in several European countries including France and United Kingdom is now again threatened by this aphid-vectored viral disease. In this review, we summarize the current knowledge on the YDV pathosystem, describe management options against YDD, analyse the impacts of the neonicotinoid ban in Europe, and consider future strategies to control YDV. © 2020 Society of Chemical Industry.