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INRAE 24, chemin de Borde Rouge –Auzeville – CS52627 31326 Castanet Tolosan cedex - France
Since 1st September 2018, I have been working as a Research Scientist in the team ‘Virology’ of the Plant Pathology Research Unit (INRAE, Avignon). My main research interest focuses on the identification of efficient, cost-effective and durable strategies to manage plant diseases and especially those caused by viruses on vegetable crops.
RESEARCH ACTIVITIES
I use spatiotemporal simulation models, complemented with laboratory and glasshouse experiments, as well as statistical analyses of epidemiological data. These experiments and field data result in the acquisition of crucial knowledge on the biology of the interactions between host plants, pathogens and possibly their vectors. Indeed, these knowledge give the possibility to calibrate model parameters or test model predictions, and can be very helpful to identify promising control methods. Finally, it is crucial for me to identify strategies that match with farmers’ needs, and communicate them in such a way that my researches have an impact on the real world.
1. Modelling control strategies of epidemics
Simulation models are very useful to optimise management strategies of epidemics, and circumvent the ethical, legal, logistical and economic constraints associated with experiments at large spatiotemporal scales. My models simulate the epidemiological dynamics of pathogens in cultivated landscapes under disease management, and aim at optimising management strategies. However, pathogens have an extraordinary evolutionary potential that allows them to overcome control methods employed in the field. This is particularly the case with the deployment of plant resistance. Thus, because they include pathogen evolution, the demo-genetic models I use are of great interest, and enable the identification of strategies that are both efficient and durable to manage plant diseases.
In collaboration with the BioSP (Biostatistics and spatial processes, INRAE PACA Avignon) and CSIRO (Canberra, Australia), I contributed to the development of the package R landsepi (Landscape Epidemiology and Evolution), which can be downloaded here [https://cran.r-project.org/package=landsepi]. This package allows the simulation of a panel of resistance deployment strategies against plant pathogens, especially:
rusts of wheat, caused by fungi of the genus Puccinia
downy mildew of grapevine, caused by the oomycota Plasmopara viticola
black sigatoka of banana, caused by the fungus Pseudocercospora fijiensis
cucumber mosaic virus (CMV) and potato virus Y (PVY) on pepper
Diverse strategies can be compared with respect to their epidemiological (plant health), evolutionary (resistance durability) and economic (cost efficiency) performance. The package also includes a shiny web interface for pedagogical purpose.
Resistance deployment strategies. A durable management of plant resistance includes the choice of the resistance source, and its wise spatiotemporal deployment at different nested scales, with the aim of mitigating pathogen evolution towards resistance breakdown. Adapted from Rimbaud L., Fabre F., Papaïx J., Moury B., Lannou C., Barrett L. and Thrall P. (2021). Models of plant resistance deployment. Annu. Rev. Phytopathol. 59:125-152.
Examples of simulated landscapes allocated with a 3-cultivar mosaic. An algorithm controls the relative proportion and degree of spatial aggregation of the different cultivars. From Rimbaud L, Papaïx J, Rey JF, Barrett LG and Thrall PH (2018). Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens. PLoS Comput. Biol. 14:e1006067.
SEIR architecture of the model. Healthy hosts can be infected by propagules. Following a latent period, infectious hosts produce new propagules which may mutate and disperse across the landscape. At the end of the infectious period, infected hosts become epidemiologically inactive. A web pedagogical interface of SEIR models is available here [https://loup.shinyapps.io/loup_demo_shiny/]. Adapted from Rimbaud L, Papaïx J, Barrett LG, Burdon JJ and Thrall PH (2018). Mosaics, mixtures, rotations or pyramiding: What is the optimal strategy to deploy major gene resistance? Evol. Appl. 11(10):1791-1810.
2. Understanding plant-virus-vector interactions via experiments
A fine understanding of the biology of interaction between pathogens, hosts and vectors is necessary to identify relevant control strategies.
2.1 Management of CMV epidemics in Espelette
It is crucial to identify the key factors of epidemic spread. It is the objective of my researches on the cucumber mosaic virus (Bromoviridae, Cucumovirus), which recently emerged on Espelette pepper crops, causing severe damages. Based on field sampling, laboratory diagnostic tools (using serological and molecular methods) and statistical analyses, I explore the different dissemination pathways of CMV in the Basque Country (Southwestern France).
Cucumber mosaic virus is a tri-partite virus composed of 3 particles, each of them containing a positive single stranded RNA. It infects a very wide range of host plants, among which pepper. It is transmitted by the seed of some host plants, and by more than 80 species of aphids in the non-persistent mode.
2.2 Evaluation of varietal resistance of pepper against PVY
Resistance is an interesting way to inhibit these interactions. Plant resistance is a decrease (possibly complete) in the ability of the parasite to infect, colonise or exploit the host for its own development. Numerous molecular mechanisms of plant resistance to pathogens have been elucidated, however very few data are available to understand the effect of such resistances on the main steps of parasitic infectious cycles. Such data are essential to calibrate simulations models (for example steps 1 to 4 of the SEIR architecture, see above) destined to evaluate different types of varietal resistance. My experiments aim at assessing different types of resistance to potato virus Y(Potyviridae, potyvirus) in pepper (Capsicum annuum).
Our first results show that the aphid-mediated PVY infection rate (step 1) is slightly lower in a resistant accession (Perennial) than in a susceptible accession (Yolo Wonder). Nevertheless, this difference is too small to explain why Perennial is so resistant in the field; this accession must certainly affect other steps of the viral infectious cycle.
TRANSFER OF KNOWLEDGE
1. Teaching
I teach yearly on these two main themes: - bases of phytopathology - mathematical approaches to assess resistance deployment strategies in these institutes: - Avignon Université : Gestion et Qualité des Productions Végétales (GQPV, M1) Ingénierie Filière Fruits & Légumes (I2FL, M1) - Université Paris-Saclay: De l’Agronomie à l’AgroEcologie (AAE, M2) - Montpellier SupAgro: Protection des Plantes et Environnement (PPE, M2) Amélioration des plantes et ingénierie des plantes tropicales et méditerranéennes (APIMET & SEPMET, M2) - Swedish University of Agricultural Sciences: Plant biology for breeding & protection (M2)
2. PhD supervision
Since 2022 : Elise Lepage (AgroParisTech IPEF, co-supervisor): Emergences at the agro-ecological interface: the role of wild reservoirs on epidemic evolutive dynamics of pathogenss.
3. Encadrement post-doctorante
Since 2021 : Marta Zaffaroni (INRAE, co-supervisor): Resistance genes diversification strategies to manage plant pathogens in agro-ecosystems: theoretical approaches and application to French vineyard landscapes.
4. Internship supervision
2023: Manon Couty (M2 INSA Lyon, co- supervisor): Spatio-temporal modelling of epidemics: how to diversify agricultural landscapes?
2022: Ulysse Caromel (L3 Avignon Université, main supervisor): Image analysis to measure pepper resistance to PVY
2021:
Elise Lepage (M2 AgroParisTech, main supervisor): Itinerary of a fluorescent virus: studying pepper resistance to potato virus Y.
Pauline Bouvet (2nde, Cité Scolaire du Diois, main supervisor)): Internship for professional immersion
2020:
Pierre Mustin (M2, main supervisor):Evaluation of plant resistance to viral transmission
Clarisse Vincent (M2, co- supervisor): Maintaining resistance durability to black sigatoka in new banana cultivars
2019: Jean-Loup Gaussen (M2, co- supervisor): Development of spatial tools for the R package landsepi
2014: Samuel Marchat (M1, co- supervisor): Development of an early detection protocol for the virus responsible of sharka in prunus trees
Modification date: 02 July 2024 | Publication date: 04 May 2023 | By: RIMBAUD Loup
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