Epidemiology, ecology, evolution

Designing optimal strategies for epidemiosurveillance and integrated plant health management requires an understanding of the interactions between the spatio-temporal heterogeneity of the environmental matrix, and the demographic and adaptive dynamics of pest populations. These interactions are multiple and take place across a wide range of spatial scales, from the plant to the planet. Our research concerns various phytopathogenic agents (bacteria, fungi, viruses), beneficial micro-organisms (phages) as well as insect pests and vectors, and draws on the multi-disciplinary skills present in the unit, our national and international collaborations and the deployment of experimental and field approaches.

Figure adapted from Fabre et al. in Lannou C., Roby D., Ravigné V., Hannachi M., Moury B., 2021. L'immunité des plantes. Pour des cultures résistantes aux maladies, éditions Quæ, Versailles, 392 p.

MAIN OBJECTIVES

I - Understanding and predicting crop pest population dynamics from plant to landscape scale

Identifying the diversity of reservoirs, including those outside cultivated environments

Knowledge of the various habitats (e.g. wild host plants, crop debris, litter, water, air, soil, inert surfaces) that support pest populations, not only in the immediate vicinity of cultivated plots, but also at the scale of production basins and even beyond, is a key factor in understanding epidemiological dynamics. These habitats are possible sources of inoculum for crop (re)infestation via local and long-distance dispersal processes. These habitats also exert different selection pressures that influence the evolutionary dynamics of pests and their adaptive potential. Thus, understanding the epidemiological role of reservoirs can help identify at-risk contexts, relevant for consideration in epidemio-surveillance schemes.

Diversity of pest reservoirs, including those outside cultivated environments

Inferring the dispersal processes involved in the colonization of agricultural areas

Estimating local dispersal, i.e. between plots and between crops and potential reservoir habitats present in the vicinity (e.g. flows with ground cover, weeds or alternative host patches dispersed in the environmental matrix), relies on the collection of demographic data (e.g. abundance/prevalence) and the production of molecular data to implement population genetics and spatial modeling approaches in epidemiology and population dynamics.

llustration of the sampling plan for peppers and weeds from plot to production basin. Corine Land Cover 2018 map base

The estimation of long-range dispersion, assisted by air masses, water flows and trade in infested or infected goods, relies on the calculation of spatio-temporal networks of potential connectivity, e.g. Tropolink approach (Richard et al. 2023), based on the HYSPLIT air mass trajectory reconstruction model, for airborne dispersion.

Illustration of potential  long-range dispersion routes via water flows (left, Durance basin, Morris et al. 2023) and air flows (right, trajectories of air masses arriving at Avignon for a given period of time, with the trajectories selected in red after filtering by various criteria, e.g. maximum air mass altitude)

Identifying and prioritizing key biotic and abiotic environmental factors in the emergence, spread and intensity of epidemics

The various biotic and abiotic conditions considered in our projects include processes related to the host plant (e.g. genotype, age, physiology), the presence of microbial communities (e.g. fungi, bacteria, phages), nutritional status (e.g. nutrient and water inputs), agricultural practices, landscape structure (e.g. wild compartment), and climate (e.g. temperature, precipitation, relative humidity). This work is carried out using a combination of descriptive analysis of spatial or spatio-temporal patterns (e.g. demographic, epidemiological and genetic), machine learning methods and statistical and mechanistic modeling approaches.

Illustration of the multiplicity of biotic and abiotic factors that can affect the severity of plant diseases

Hypotheses on the role of the wild compartment in epidemic dynamics

The conceptual framework developed within these projects is used to characterize the impact of (a)biotic factors on the risk of frost, which is particularly important for fruit trees. Work is being carried out on apricot trees to understand the origin of ice formation and distinguish the role of internal factors (i.e. linked to the plant itself) or external factors (i.e. linked to ice-causing bacteria) in this nucleation process.

Illustration of the interactions involved in the risk of organ freezing in fruit trees

II - Studying the adaptive potential of bioaggressors and the evolution of their pathogenicity

Elucidating the molecular determinants of functional traits of phytopathogenic bacteria and their phages

We use an innovative method (Tn-seq) that combines the use of transposon insertion mutant libraries and high-throughput sequencing to reveal bacterial genes essential for growth under contrasting conditions. This type of approach makes it possible to identify the key molecular determinants for survival and maintenance of pathogenicity under different selection pressures, particularly in natural reservoirs in the absence of contact with plants (water).

Illustration of the experimental scheme associated with the comparison of bacterial mutant libraries generated by the Tn-seq method with different selection pressures (in vitro, plants, water with or without phages)

Understanding the mechanisms of host jumpomprendre les mécanismes des sauts d’hôtes

The processes of adaptation of pathogens to plant varietal resistance is relatively well known. In contrast, the ability of plant pathogens to adapt to a new species, i.e. host jumping, is much less understood despite its recognized importance in the emergence of new diseases. We are developing experimental evolutionary approaches to elucidate the possibilities of host jump in plant viruses, the associated molecular mechanisms, and the risks of emergence of virus mutants and of cross-adaptation, i.e. multiple host jumps caused by a single mutation.

Illustration of an experimental evolution protocol for endive necrotic mosaic virus