Objectif The immune system within each individual host destroys viruses, which manage to escape immunity on the global scale. Recent experiments show population-level responses of both immune repertoires and viruses, and a history dependence of their functional phenotypes. This constrained long-term co-evolution of immune receptor and viral populations is a stochastic many-body problem occurring at many scales, in which the response emerges based on the past states of both the repertoire and viral populations. STRUGGLE infers the details of viral-immune receptor interactions from functional datasets to obtain a predictive statistical model of co-evolution between immune repertoires and viruses.STRUGGLE covers the many scales of immune-virus interactions: from the molecular level, analyzing high-throughput mutational screens of libraries of antibodies binding a given antigen, through the population-level response of immune repertoires, analyzing next-generation sequencing of vaccine-stimulated whole repertoires, to the population level, modeling the long term co-evolution of both repertoires and viruses.STRUGGLE combines a statistical data analysis approach with cross-scale many-body physics to: - build a molecular model for antigen-receptor binding;- learn statistical models for repertoire-level response to viral antigen stimulation;- validate dynamical models of interactions between antigen and immune receptors;- theoretically evaluate the predictive power of the immune system and viruses;- and predict virus strains and immune responses based on past infections.The outcomes of STRUGGLE include the quantitative characterization of the human T-cell response to flu vaccines, with implications for vaccination strategies, and the trout B-cell response to life-threatening rhabdoviruses, which aids vaccine design for fish, with wide use in agriculture. The statistical properties of the co-evolutionary process are needed for informed development of immunotherapies. Champ scientifique natural sciencesbiological sciencesmicrobiologyvirologynatural sciencesbiological sciencesevolutionary biologymedical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsvaccinesnatural sciencesmathematicsapplied mathematicsstatistics and probabilitymedical and health sciencesbasic medicineimmunologyimmunotherapy Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Thème(s) ERC-2016-COG - ERC Consolidator Grant Appel à propositions ERC-2016-COG Voir d’autres projets de cet appel Régime de financement ERC-COG - Consolidator Grant Institution d’accueil CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS Contribution nette de l'UE € 1 909 750,00 Adresse RUE MICHEL ANGE 3 75794 Paris France Voir sur la carte Région Ile-de-France Ile-de-France Paris Type d’activité Research Organisations Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 1 909 750,00 Bénéficiaires (1) Trier par ordre alphabétique Trier par contribution nette de l'UE Tout développer Tout réduire CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS France Contribution nette de l'UE € 1 909 750,00 Adresse RUE MICHEL ANGE 3 75794 Paris Voir sur la carte Région Ile-de-France Ile-de-France Paris Type d’activité Research Organisations Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 1 909 750,00