Summary
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.
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.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/724208 |
| Start date: | 01-11-2017 |
| End date: | 31-10-2023 |
| Total budget - Public funding: | 1 909 750,00 Euro - 1 909 750,00 Euro |
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Original description
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.
Status
SIGNEDCall topic
ERC-2016-COGUpdate Date
27-04-2024
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