Description du projet
La transmission de maladies dans les groupes sociaux
Le risque d’apparition de maladies peut augmenter dans les organismes sociaux vivant en groupes denses, où les agents pathogènes peuvent se transmettre rapidement entre les hôtes. Selon la théorie, la dynamique des maladies doit dépendre de la composition d’un groupe social et de la structure de son réseau social. Cependant, les données empiriques manquent. L’épidémiologie expérimentale est entravée par l’absence de systèmes d’étude permettant de rechercher le lien causal entre la composition des groupes, la structure des réseaux sociaux et la transmission des maladies. Le projet EPIDEMIC, financé par l’UE, utilisera un système original basé sur les caractéristiques biologiques uniques de la fourmi clonale. Contrairement aux autres fourmis, cette espèce est privée de reines et se reproduit par clonage, ce qui permet de contrôler des aspects importants de la composition de la colonie. Le projet utilisera des techniques automatisées pour suivre le comportement, dans le but de détecter les caractéristiques qui protègent les organismes sociaux contre les maladies infectieuses.
Objectif
The risks and impact of disease are exacerbated in social organisms, which live in dense groups wherein pathogens can rapidly propagate. Theoretical epidemiology predicts that disease dynamics will depend in large part on a group's social interaction network, but empirical data are scarce. Experimental epidemiology is currently hampered by a lack of study systems that would enable a rigorous investigation of the causal link between network structure and disease transmission.
I will tackle this question using a novel system, the clonal raider ant, a social insect whose unique biology affords unparalleled control over the main aspects of colony composition that are thought to modulate social network structure, and therefore, disease transmission. My approach will combine cutting-edge automated techniques for behavioral tracking with molecular tools, and develop new methods to monitor transmission in real time. In a first step, I will create empirical networks that are theoretically predicted to vary in transmission risk and map individual immune function onto these networks, to measure the prophylactic network properties that might reduce disease transmission. Second, I will test if experimental increases in immune activity induce changes in behavior that are relevant for disease transmission, to measure inducible network properties. Finally, I will inoculate colonies with nematodes and quantify infection propagation in real time. This will allow me to compare various types of social networks (healthy, immune-activated, infected), to probe the link between behavior and immunity, and to experimentally test predictions from theoretical epidemiology.
This project takes an integrative approach—from individual immunity to collective behavior—to uncover the properties of social groups that protect them against disease. By linking theoretical epidemiology to real-world disease dynamics, it will push the limits of our ability to predict disease dynamics in social groups.
Champ scientifique
Programme(s)
Thème(s)
Régime de financement
ERC-STG - Starting GrantInstitution d’accueil
80539 Munchen
Allemagne