Gaël Thébaud

Integrating genetic and epidemiological data to determine transmission pathways of foot-and-mouth disease virus

Estimating detailed transmission trees that reflect the relationships between infected individuals or populations during a disease outbreak often provides valuable insights into both the nature of disease transmission and the overall dynamics of the underlying epidemiological process. These trees may be based on epidemiological data that relate to the timing of infection and infectiousness, or genetic data that show the genetic relatedness of pathogens isolated from infected individuals. Genetic data are becoming increasingly important in the estimation of transmission trees of viral pathogens due to their inherently high mutation rate. Here, we propose a maximum-likelihood approach that allows epidemiological and genetic data to be combined within the same analysis to infer probable transmission trees. We apply this approach to data from 20 farms infected during the 2001 UK foot-and-mouth disease outbreak, using complete viral genome sequences from each infected farm and information on when farms were first estimated to have developed clinical disease and when livestock on these farms were culled. Incorporating known infection links due to animal movement prior to imposition of the national movement ban results in the reduction of the number of trees from 41 472 that are consistent with the genetic data to 1728, of which just 4 represent more than 95% of the total likelihood calculated using a model that accounts for the epidemiological data. These trees differ in several ways from those constructed prior to the availability of genetic data.

Beyond the Consensus: Dissecting Within-Host Viral Population Diversity of Foot-and-Mouth Disease Virus by Using Next-Generation Genome Sequencing

ABSTRACT 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.

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.

Eburicol 14α-demethylase gene (CYP51) polymorphism and speciation in Botrytis cinerea

Botrytis cinerea (anamorph of Botryotinia fuckeliana) is a filamentous ascomycete that causes grey mould especially on grapevine. Based on the presence or the absence of two transposable elements (Boty and Flipper) two sibling sympatric populations named transposa and vacuma have been described. Among the vacuma population, some strains (designated HydR1) were found to be resistant to fenhexamid (a sterol C-4 demethylase inhibitor) and to show an increased sensitivity to 14α-demethylase inhibitors (DMIs). In order to assess whether or not mutations at the target gene level (CYP51) could underlie increased sensitivity to DMIs in HydRl strains, we cloned the CYP51 gene and determined its DNA sequence in various B. cinerea strains. The gene was highly polymorphic, with mutations detected at 58 positions in the 35 strains analysed. The polymorphisms did not discriminate between transposa and vacuma strains, but did distinguish between HydRl and non-HydR1 ones. Two expressed mutations were present in all HydRl strains, namely phenylalanine to leucine at position 15 of the inferred protein, and serine to asparagine at position 105. These data, combined with the existence of morphological differences and somatic incompatibility between HydR1 and non-HydR1 strains, suggest that these two groups comprise distinct genetic entities.

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.

Sharka Epidemiology and Worldwide Management Strategies: Learning Lessons to Optimize Disease Control in Perennial Plants

Many plant epidemics that cause major economic losses cannot be controlled with pesticides. Among them, sharka epidemics severely affect prunus trees worldwide. Its causal agent, Plum pox virus (PPV; genus Potyvirus), has been classified as a quarantine pathogen in numerous countries. As a result, various management strategies have been implemented in different regions of the world, depending on the epidemiological context and on the objective (i.e., eradication, suppression, containment, or resilience). These strategies have exploited virus-free planting material, varietal improvement, surveillance and removal of trees in orchards, and statistical models. Variations on these management options lead to contrasted outcomes, from successful eradication to widespread presence of PPV in orchards. Here, we present management strategies in the light of sharka epidemiology to gain insights from this worldwide experience. Although focused on sharka, this review highlights more general levers and promising approaches to optimize disease control in perennial plants.

Observing micro-evolutionary processes of viral populations at multiple scales

Advances in sequencing technology coupled with new integrative approaches to data analysis provide a potentially transformative opportunity to use pathogen genome data to advance our understanding of transmission. However, to maximize the insights such genetic data can provide, we need to understand more about how the microevolution of pathogens is observed at different scales of biological organization. Here, we examine the evolutionary processes in foot-and-mouth disease virus observed at different scales, ranging from the tissue, animal, herd and region. At each scale, we observe analogous processes of population expansion, mutation and selection resulting in the accumulation of mutations over increasing time scales. While the current data are limited, rates of nucleotide substitution appear to be faster over individual-to-individual transmission events compared with those observed at a within-individual scale suggesting that viral population bottlenecks between individuals facilitate the fixation of polymorphisms. Longer-term rates of nucleotide substitution were found to be equivalent in individual-to-individual transmission compared with herd-to-herd transmission indicating that viral diversification at the herd level is not retained at a regional scale.

A novel cloning strategy for isolating, genotyping and phenotyping genetic variants of geminiviruses

BackgroundViruses of the genus Begomovirus (Geminiviridae) are emerging economically important plant viruses with a circular, single-stranded DNA genome. Previous studies have shown that geminiviruses and RNA viruses exhibit similar mutation frequencies, although geminiviruses are replicated by host DNA polymerases and RNA viruses by their own virus-encoded error-prone RNA-dependent RNA-polymerase. However, the phenotypic effects of naturally occurring mutations have never been extensively investigated in geminiviruses, particularly because, to be infectious, cloned viral genomes usually require sub-cloning as complete or partial tandem repeats into a binary vector from Agrobacterium tumefaciens.ResultsUsing Tomato yellow leaf curl virus (TYLCV), we show here that infectivity can be obtained when only a 41-nucleotide region containing a highly conserved stem-loop is repeated. A binary vector containing this 41-nt region and a unique restriction site was created, allowing direct cloning of infectious monomeric viral genomes provided that they harbour the same restriction site at the corresponding nucleotide position. This experimental system, which can be transferable to other geminiviruses, was validated by analysis of the phenotypic effect of mutations appearing in TYLCV genomes in a single tomato host plant originally inoculated with a unique viral sequence. Fourteen full-length infectious genomes extracted from this plant were directly cloned and sequenced. The mutation frequency was 1.38 × 10-4 mutation per nucleotide sequenced, similar to that found previously for another begomovirus by sequencing PCR-amplified partial sequences. Interestingly, even in this minimal pool of analysed genomes, mutants with altered properties were readily identified, one of them being fitter and reducing plant biomass more drastically than the parental clone.ConclusionThe cloning strategy presented here is useful for any extensive phenotyping of geminivirus variants and particularly of artificially generated mutants or recombinants.

Investigating Disease Spread between Two Assessment Dates with Permutation Tests on a Lattice

ABSTRACT Mapping and analyzing the disease status of individual plants within a study area at successive dates can give insight into the processes involved in the spread of a disease. We propose a permutation method to analyze such spatiotemporal maps of binary data (healthy or diseased plants) in regularly spaced plantings. It requires little prior information on the causes of disease spread and handles missing plants and censored data. A Monte Carlo test is used to assess whether the location of newly diseased plants is independent of the location of previously diseased plants. The test takes account of the significant spatial structures at each date in order to separate nonrandomness caused by the structure at one date from nonrandomness caused by the dependence between newly diseased plants and previously diseased plants. If there is a nonrandom structure at both dates, independent patterns are simulated by randomly shifting the entire pattern observed at the second date. Otherwise, independent patterns are simulated by randomly reallocating the positions of one group of diseased plants. Simulated and observed patterns of disease are then compared through distance-based statistics. The performance of the method and its robustness are evaluated by its ability to accurately identify simulated independent and dependent bivariate point patterns. Additionally, two realworld spatiotemporal maps with contrasting disease progress illustrate how the tests can provide valuable clues about the processes of disease spread. This method can supplement biological investigations and be used as an exploratory step before developing a specific mechanistic model.

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.