E-SPACE: Improving epidemiosurveillance of Mediterranean ...networks on epidemics, pathogen fitness...
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Technical and scientific training Formalized recommendations to partners Optimized protocols for disease elimination Diagnostic tools for pathogen detection and identification Epidemiological and evolutionary models and associated software Epidemiological databases on target pathogens Metagenomics databases of mirobes infecting germplasm collections, crops and their environment Deciphering routes of past emergences Objectives • identify source populations • date host shifts, founding events • estimate effective population sizes, migration • infer propagation modes Actions • analyze current population samples • analyze ancient DNA from herbariums • adapt and test inference methods DNA from ancient samples might help calibrating methods and reveal ancient states of pathogens Pop2 Pop3 Pop1 Pop3 Pop1 Pop2 Pop1 Pop3 Pop2 Events such as bottlenecks, divergence, admixture, etc. can be inferred through Approximate Bayesian Computing Introduction scenarios for Magnaporte oryzae revealed a more complex inoculum exchange system than expected Evaluating present determinants of adaptation Objectives • apprehend epidemiological and evolutionary parameters of emergence • optimize ressource allocation between pre- emergence and post-emergence situations in various epidemiological scenarios Actions • characterize host, vector niches • identify molecular determinants of adaptation • measure impact of adaptation to fitness improve epidemiological models for a reliable prediction of emergence › before emergence: define the required conditions for a generic or specific epidemiosurveillance › after emergence: how can real time data be assimilated to models to improve surveillance strategies? ? ? ? ? Measuring the fitness of ALCV on alternative aphid vectors and legume hosts will anticipate vector and host shifts Exploring potential reservoirs and emergence scenarios Objectives • understand how phytobiome-plant-environment interactions drive emergence or non-emergence • understand the impact of biotic diversity, farmer’s community mechanisms, etc. on plant health Actions • develop metagenomics tools for a global diagnosis • characterize microbiome and virome of plant propagating material • produce metagenomic snapshots of microbial diversity of Mediterranean and tropical crops and their environment • model stable ecosystems behavior where disease incidence is remarkably low (e.g. "Eternal Rice" in Yuanyang) The Yuanyang terraces: a case of sustainable blast resistance The effect of landscape, biodiversity and social networks on epidemics, pathogen fitness and durability can be modeled Collecting samples in the South-African Fynbos for viral metagenomics Optimizing epidemiosurveillance networks E-SPACE: a scientific network dedicated to Epidemio-Surveillance of PAthogens on Crops and their Environment Objectives • share expertise between researchers, quarantine authorities, extension scientists • develop higher education programs to train new scientists • transfer new tools and protocols Actions • important education and capacity building initiative in the South-Western Indian Ocean • scientific exchanges between Labex Agro units, regulators, extension scientists Training young scientists is essential for a future efficient epidemiological surveillance Sharing and improving our knowledge on pathological and epidemiological processes underlying plant pathogen emergence in order to facilitate epidemiosurveillance 3 research units in Montpellier 1 research unit in La Réunion International Lab in Vietnam International Lab in Burkina Faso E-SPACE: Improving epidemiosurveillance of Mediterranean and tropical plant diseases http://www6.inra.fr/e-space Pr Claire Neema (UMR BGPI), Dr Lionel Gagnevin (UMR IPME) Contact: [email protected] Mapping of populations status in different areas will help orient surveillance Pathosystems: Rice: M. oryzae, X. oryzae, Rice Yellow Mottle Virus, Meloidogyne. Banana: M. fijiensis, X. v. pv. musacearum, Banana Streak Virus. Cacao: P. megakarya, Cacao Swollen Shoot Virus. Prunus: Plum pox virus, Candidatus Phytoplasma prunorum, Xylella fastidiosa. Tomato: Begomovirus, X. vesicatoria, X. euvesicatoria. Citrus: X. c. pv. citri. Cassava: Begomovirus, X. a. pv. manihotis. Potato: R. solanacearum. Maize: Mastrevirus. Mango: X. c. pv. mangiferaeindicae. Alfalfa: Alfalfa leaf curl virus Transfer of methods and protocols to extension labs will allow harmonization of surveillance in large areas Context: Cultivated plants are subject to diseases caused by viruses, bacteria, fungi, nematodes…In the recent years there has been an increase in the spread of existing diseases as well as the emergence of new diseases or shift of existing diseases to new hosts. This increase is probably due to factors such as globalization (which increases the movements of pathogens worldwide), climate change (which allows pathogens from warm regions to invade temperate regions), and the evolution of pathogens (where they may adapt to new hosts). Chemical control is highly inefficient against such diseases and there is a general trend for the reduction of pesticide use (eg. “Plan ECOPHYTO”). Therefore control of plant diseases is performed through alternate strategies.
Transcript of E-SPACE: Improving epidemiosurveillance of Mediterranean ...networks on epidemics, pathogen fitness...
Technical and scientific
training
Formalized recommendations
to partners
Optimized protocols for
disease eliminationDiagnostic tools for pathogen detection
and identification
Epidemiological and evolutionary models
and associated software
Epidemiological databases on
target pathogens
Metagenomics databases of mirobes infecting germplasm
collections, crops and their environment
Deciphering routes of past emergencesObjectives• identify source populations• date host shifts, founding events • estimate effective population sizes, migration• infer propagation modesActions• analyze current population samples• analyze ancient DNA from herbariums• adapt and test inference methods
DNA from ancient samples might help calibrating methods and reveal ancient states of pathogens
Pop2 Pop3 Pop1 Pop3 Pop1 Pop2 Pop1 Pop3 Pop2
Events such as bottlenecks, divergence, admixture, etc. can be inferred through
Approximate Bayesian Computing
Introduction scenarios for Magnaporte oryzae revealed a more complex inoculum exchange
system than expected
Evaluating present determinants of adaptationObjectives• apprehend epidemiological and evolutionary
parameters of emergence• optimize ressource allocation between pre-
emergence and post-emergence situations in various epidemiological scenarios
Actions• characterize host, vector niches• identify molecular determinants of adaptation• measure impact of adaptation to fitness
improve epidemiological models for a reliable prediction of emergence
› before emergence: define the required conditions for a generic or specific epidemiosurveillance
› after emergence: how can real time data be assimilated to models to improve surveillance strategies?
?? ? ?
Measuring the fitness of ALCV on alternative aphid vectors and legume hosts will anticipate vector and host shifts
Exploring potential reservoirs and emergence scenariosObjectives• understand how phytobiome-plant-environment
interactions drive emergence or non-emergence• understand the impact of biotic diversity,
farmer’s community mechanisms, etc. on plant health
Actions• develop metagenomics tools for a global
diagnosis• characterize microbiome and virome of plant
propagating material• produce metagenomic snapshots of microbial
diversity of Mediterranean and tropical crops and their environment
• model stable ecosystems behavior where disease incidence is remarkably low (e.g. "Eternal Rice" in Yuanyang)
The Yuanyang terraces: a case of sustainable blast resistance
The effect of landscape, biodiversity and social networks on epidemics, pathogen fitness and
durability can be modeled
Collecting samples in the South-African Fynbos for viral metagenomics
Optimizing epidemiosurveillance networksE-SPACE: a scientific network dedicated to Epidemio-Surveillance of PAthogens on Crops and their EnvironmentObjectives• share expertise between researchers,
quarantine authorities, extension scientists• develop higher education programs to train
new scientists• transfer new tools and protocolsActions • important education and capacity building
initiative in the South-Western Indian Ocean• scientific exchanges between Labex Agro units,
regulators, extension scientists
Training young scientists is essential for a future efficient epidemiological surveillance
Sharing and improving our knowledge on pathological and epidemiological processes underlying plant pathogen emergence in order to facilitate epidemiosurveillance
3 research unitsin Montpellier
1 research unitin La Réunion
International Labin Vietnam
International Labin Burkina Faso
E-SPACE: Improving epidemiosurveillance of Mediterranean and tropical plant diseases
http://www6.inra.fr/e-spacePr Claire Neema (UMR BGPI), Dr Lionel Gagnevin (UMR IPME)Contact: [email protected]
Mapping of populations status in different areas will help orient
surveillance
Pathosystems: Rice: M. oryzae, X. oryzae, Rice Yellow Mottle Virus, Meloidogyne. Banana: M. fijiensis, X. v. pv. musacearum, Banana Streak Virus. Cacao: P. megakarya, Cacao Swollen Shoot Virus. Prunus: Plum pox virus, Candidatus Phytoplasma prunorum, Xylella fastidiosa.
Tomato: Begomovirus, X. vesicatoria, X. euvesicatoria. Citrus: X. c. pv. citri. Cassava: Begomovirus, X. a. pv. manihotis. Potato: R. solanacearum. Maize: Mastrevirus. Mango: X. c. pv. mangiferaeindicae. Alfalfa: Alfalfa leaf curl virus
Transfer of methods and protocols to extension labs will allow harmonization of
surveillance in large areas
Context:Cultivated plants are subject to diseases caused by viruses, bacteria, fungi, nematodes…In the recent years there has been an increase in the spread of existing diseases as well as the emergence of new diseases or shift of existing diseases to new hosts.This increase is probably due to factors such as globalization (which increases the movements of pathogens worldwide), climate change (which allows pathogens from warm regions to invade temperate regions), and the evolution of pathogens (where they may adapt to new hosts).Chemical control is highly inefficient against such diseases and there is a general trend for the reduction of pesticide use (eg. “Plan ECOPHYTO”). Therefore control of plant diseases is performed through alternate strategies.
