My research focuses on the sustainable management of crop plant immunity to pathogens, particularly viruses. I take a multi-disciplinary approach to this topic, focusing on the molecular interactions between plants and viruses, the genetics and evolution of viral populations, and modeling. More generally, I study certain evolutionary properties of plant viruses (host range, intensity of genetic drift during the infectious cycle, selection pressures).
Plant-virus interactions
Genetic immunity in plants, also known as resistance, is a very interesting lever for avoiding diseases or reducing their impact on the yield or quality of agricultural production. It can be highly effective, has no adverse effect on the environment or human health, and is generally specific to a given pathogen, inducing few "collateral" effects. Plant geneticists and breeders of crop varieties have focused mainly on the major plant resistance genes that confer high-level immunity.
Viruses need many components of their host cells for their infectious cycle. In particular, they hijack the host's cellular machinery through interactions between viral proteins and host proteins. The presence of mutations in plant proteins preventing interaction with the virus can thus lead to resistance.
In collaboration with Jean-Luc Gallois, Alain Palloix and Carole Caranta (GAFL unit), I have shown that the interaction between eIF4E proteins involved in messenger RNA translation in plants (tomato, pepper) and VPg proteins linked to the genome of certain viruses was decisive for the infectivity of these viruses and the immunity of these plants (Fig. 1). I have also worked on other types of plant-virus interactions that function differently from eIF4E-VPg interactions (Janzac et al., 2010, Molecular Plant-Microbe Interactions 23:823-830; Moury et al., 2023, Viruses 15:1081). Knowledge of these interactions also tells us about the potential durability of immunity.
Fig. 1: The eukaryotic translation initiation protein complex and its role in virus resistance. On the right: the virus genome and VPg protein depicted in red corresponds to a potyvirus. The plant proteins of the translation initiation complex are represented in other colors. On the left: a schematic representation of the key role of eIF4E and VPg in plant immunity and virus infection. AAAAAA: poly-adenylated tail; eIF : eukaryotic initiation factor; Mut: mutated version of eIF4E or VPg; PABP : poly-A binding protein; VPg : viral protein genome-linked; WT : wild-type. After Ayme et al., 2006, Molecular Plant-Microbe Interactions 19:557-563 ; Charron et al., 2008, Plant Journal 54:56-68
Sustainability of plant immunity
A question often asked by variety breeders is how durable the resistance present in their varieties will be, i.e. how many years plant immunity will endure in the face of the evolutionary potential of targeted pathogens. For the major resistance genes, the durability potential is extremely variable, ranging from a few months to decades. The number of mutations required for the pathogen to adapt to the plant's immunity and the adaptive cost induced by this (these) mutation(s) partially explain these differences.
However, even for plants possessing a major resistance gene with low durability potential, all hope is not lost! In the case of pepper immunity to a virus, we have demonstrated that it is possible to considerably increase the durability potential of a major gene by combining it with other partial-effect resistance genes (Figure 2; Palloix et al., 2009, The New Phytologist, 183:190-199). Several mechanisms seem to be jointly responsible for this increase in durability potential, notably the effects of natural selection and genetic drift exerted by the plant on the viral population infecting it (Figure 3). These promising effects deserve to be explored more widely in other plant species and pathogens.
Figure 2. Variation in the adaptation rate of a virus to a major-effect resistance gene in pepper. Distribution of the adaptation rate of PVY (potato virus Y) among 150 pepper lines carrying the pvr23resistance gene (percentage of inoculated plants where virus adaptation was observed one month after inoculation). Based on Quenouille et al., 2014, Heredity 112:579-587.
Figure 3: Contrasting effects of genetic drift within a virus population (potato virus Y: PVY) when infecting three pepper varieties. Top: Variation in the number of primary infection foci of PVY (tagged with fluorescent protein) during mechanical inoculation. Varieties showing a low number of infection foci also induce more stringent genetic drift within the viral populations infecting them. Bottom: Variation in evolutionary trajectories undergone by a composite PVY population during plant colonization. For each variety, the first eight colored bars represent the frequencies of five PVY variants (different colors) in each of the eight plants, and the last bar represents the average of the eight plants. The evolution over time of the average variant frequencies indicates the intensity of selection (more or less rapid loss of the least adapted variants). The variability of variant frequencies between the 8 plants at 30 days after inoculation indicates the intensity of genetic drift. Based on Rousseau et al., 2017, PLoS Pathogens 13:e1006702and Tamisier et al., 2017, Journal of General Virology 98:1923-1931
More generally, little is known about partial-effect resistances, particularly in terms of mechanisms of action, genes involved, specificity of interaction with targeted pathogens (or pests) and durability potential. For these last two aspects, the analysis of quantitative interaction matrices between plants and their pathogens can be highly instructive. Using datasets provided by numerous collaborators and appropriate algorithms, I was able to analyze the general structure of around thirty such matrices (Figure 4; Moury et al., 2021, Peer Community Journal 1:e44). This type of analysis can help guide the choice of varieties or complementary resistance genes to which pathogens will have the least "chance" of adapting globally, and the strategies for deploying these varieties in the agricultural landscape.
Figure 4. Interaction matrix between melon (Cucumis melo) and powdery mildew (Podosphaera xanthii). Each of 19 melon genotypes (rows) was inoculated with each of 26 powdery mildew strains (columns). This matrix shows a highly nested structure, indicating a gradation of virulence in the parasite and a gradation of resistance in the host plant, but little or no specificity of interaction between plant and parasite. Adapted from Moury et al., 2021, Peer Community Journal 1:e44
Exploring the most favorable strategies for deploying resistant varieties in terms of efficacy and sustainability is very difficult to achieve experimentally. Mathematical modeling approaches, carried out in collaboration with Loup Rimbaud (PV unit) and Frédéric Fabre (SAVE unit), are helping to identify the most promising strategies. To find out more: https://youtu.be/PfwEOeFpiKM
Effects of abiotic disturbances on plant immunity
The physical environment of plants (temperature, humidity, light, soil, etc.) can influence their immunity and the spread of pathogen-related epidemics. Current climatic and environmental changes also contribute to this, posing a threat to the stability of agricultural production. In collaboration with Véronique Lefebvre (GAFL unit), I am studying the robustness of plant immunity in the face of various environmental disturbances (Figure 5). In particular, I am investigating the genetic factors that control robustness traits in plants, and the genericity of this robustness in the face of different pathogens (viruses, oomycetes) or disturbances (temperature, water regime).
Figure 5. Two types of phenotypic robustness. Behavior of varieties with a more or less robust phenotype in two contrasting environments, Env. 1 and Env. 2 (fictitious data). Each point corresponds to an individual of the variety considered. Adapted from Félix & Barkoulas, 2015, Nature Reviews Genetics 16:483-496
MINI-CV
Since 2021: Director of the Plant Pathology unit, INRAE PACA (Avignon) (See the website INRAE)
2013-2020: Head of the Virology team in the Plant Pathology unit
2007: Research director
2000: Visiting Researcher, Danish Institute of Agricultural Sciences (Copenhagen, Denmark)
Since 1999: Mobility to Inra Avignon (Plant Pathology unit)
1997-1999: Researcher at Inra Antibes (Botany and Plant Pathology unit)
1994-1997: Thesis at Inra Avignon (Plant Breeding and Plant Pathology units)
1993: National service volunteer, CIRAD - IRA Cameroun
1992: Diploma in agricultural engineering and DEA, ENSA Rennes-Univ. Rennes II
By browsing our site you accept the installation and use cookies on your computer.
Know more
Our use of cookies
Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.
To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.
You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.
In the case of third-party advertising cookies, you can also visit the following site: https://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.
It is also possible to block certain third-party cookies directly via publishers:
Cookie type
Means of blocking
Analytical and performance cookies
Realytics Google Analytics Spoteffects Optimizely
Targeted advertising cookies
DoubleClick Mediarithmics
The following types of cookies may be used on our websites:
Mandatory cookies
Functional cookies
Social media and advertising cookies
These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.
These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.
These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.
Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times). These cookies are deleted at the end of the browsing session (when you log off or close your browser window)
Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months
Our EZPublish content management system (CMS) does not use this type of cookie.
For more information about the cookies we use, contact INRAE’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:
INRAE 24, chemin de Borde Rouge –Auzeville – CS52627 31326 Castanet Tolosan cedex - France