Estimating sharka dispersal function by stochastic spatiotemporal modelling

Plant viral diseases, and especially the ones transmitted by aerial vectors, can cause considerable yield losses. A good knowledge of the distances of spread is key to the understanding of disease dynamics. Exploratory approaches aiming at characterizing the spatiotemporal distribution of diseased plants are often used to get an insight into the distances of spread. A more powerful approach is based on stochastic spatiotemporal modelling in order to estimate the dispersal function of the disease (probability density function describing the probability for an infectious plant to infect a healthy plant at distance d). In this study, we implemented a method for estimating the dispersal function of the sharka disease. Sharka is one of the most serious diseases of stone fruit trees (Prunus sp.). It is caused by Plum pox virus (PPV, genus Potyvirus), transmitted by at least twenty different aphid species in a non persistent manner. Due to the inefficiency of insecticides and the very rare sources of resistance against the virus available in the host species, prophylactic disease control is based on the removal of the diseased trees in the orchards. Thus, a very good knowledge of the dispersal function of sharka is crucial for building epidemiological models and optimizing the strategies of surveillance and control. We adapted the methodology published by Gibson (1997) based on a Markov chain Monte Carlo (MCMC) algorithm in order to estimate sharka dispersal function from the maps of 157 contiguous peach orchards reporting the exact location and the sanitary status (asymptomatic/symptomatic) of each of the trees during six consecutive years. An estimation method based on the Gibbs sampling algorithm was developed taking into account the specificities of the dataset (more than two dates of observation, annual removal of diseased trees). This estimation algorithm was validated on simulated data and was proved to be more powerful and better adapted to large datasets than the one proposed by Gibson. Moreover, the influence of latency on the estimation of the dispersal function was quantified. This methodology was then used to estimate the dispersal function of the disease from a subset of the real dataset. The methods developed in this study are generic enough to be used and adapted for the estimation of dispersal functions of any disease transmitted in a non persistent manner, and even for diseases with similar characteristics. (Texte intégral

Long-term viral competition monitoring: a case of epidemiological rescue

Biological invasions are major threats to biodiversity and the main causes of emerging viral diseases. The ongoing spread of Tomato yellow leaf curl virus is a major concern to the sustainable tomato production throughout the world. The two main strains of TYLCV have been successively introduced in Reunion Island providing a fortuitous field experiment to study the invasion and competition of these two emerging strains in a tropical and insular environment. In this study, a seven-year field survey was performed following the introduction of the Israel strain of TYLCV (TYLCV-IL) into a niche occupied by the Mild strain of TYLCV (TYLCV-Mld). A displacement of the resident TYLCV-Mld by the newcomer TYLCV-IL was observed in this short period. To understand the factors associated with this displacement, biological traits related to fitness were measured to compare these strains. Besides demonstrating a better ecological aptitude of TYLCV-IL, which explains its rapid spread and increasing prevalence, the first estimate of the number of viral particles efficiently transmitted by an insect vector for a circulative virus was obtained. However, TYLCV-Mld persistence in the field (especially in mixed infections with TYLCV-IL) spurred further experiments regarding the effects of the mixed infections on these biological traits. Our study revealed complex interplay between these two strains of one of the most emergent plant virus following their successive introductions in the insular and tropical environment of Reunion Island. This rare case of unilateral facilitation between two pathogens led to the epidemiological rescue and maintenance of the less fit strain. (Texte intégral

Rapid accumulation and low degradation: Key parameters of Tomato yellow leaf curl virus persistence in its insect vector Bemisia tabaci

Of worldwide economic importance, Tomato yellow leaf curl virus (TYLCV, Begomovirus) is responsible for one of the most devastating plant diseases in warm and temperate regions. The DNA begomoviruses (Geminiviridae) are transmitted by the whitefly species complex Bemisia tabaci. Although geminiviruses have long been described as circulative non-propagative viruses, observations such as long persistence of TYLCV in B. tabaci raised the question of their possible replication in the vector. We monitored two major TYLCV strains, Mild (Mld) and Israel (IL), in the invasive B. tabaci Middle East-Asia Minor 1 cryptic species, during and after the viral acquisition, within two timeframes (0–144 hours or 0–20 days). TYLCV DNA was quantified using real-time PCR, and the complementary DNA strand of TYLCV involved in viral replication was specifically quantified using anchored real-time PCR. The DNA of both TYLCV strains accumulated exponentially during acquisition but remained stable after viral acquisition had stopped. Neither replication nor vertical transmission were observed. In conclusion, our quantification of the viral loads and complementary strands of both Mld and IL strains of TYLCV in B. tabaci point to an efficient accumulation and preservation mechanism, rather than to a dynamic equilibrium between replication and degradation. (Résumé d'auteur

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

The sequence diversity of viral populations within individual hosts is 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 determined by NGS, for the Inoculum, was identical to that previously determined using the Sanger method. However, NGS reveals the fine polymorphic sub-structure 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 sulphate binding and were present in both feet 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 only in a small fraction of the population and represent the progeny from recent cellular replication prior to onset of any selective pressures. We estimated an upper limit for the genome-wide mutation rate of the virus within a cell to be 7.8 x 10-4 per nt. 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

One Plant Health: Rôle des plantes sauvages dans les épidémies touchant les plantes cultivées

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

International audienceHigh-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