INTI

International Network in Theoretical Immunology

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 Obiettivo del progetto (Objective)

The main aim of this proposal is to set up an International Research Network inn Theoretical Immunology that involves both experimental and theoretical immunologists. This Network will create new collaborations and reinforce existing ones in order to develop a lasting and fruitful research cooperation between all the partners. Other objectives of this proposal are (1) Establish a lasting and fruitful research cooperation between the experimental and theoretical immunologists of the network with the aim to provide immunology with a more quantitative basis. (2) Establish a lasting and fruitful research cooperation between the different groups that work in theoretical immunology, with the aim to discuss, compare, test and validate different modelling approaches. (3) Train the new generation of theoretical immunologists, with the aim to exchange postgraduate students and research fellows, so that they benefit from the broader knowledge, skills and tools provided by the Network. (4) A final objective of the Network is to develop, by means of the Staff Exchange Scheme, four long-term directions for modelling in immunology. In particular, (i) To develop stochastic models for the motion of pathogens and of cells of the immune system, validated by comparing with experiments. (ii) To build a model of the immune system as a whole using stochastic dynamics of interacting populations. We aim to understand how the system maintains its diversity of millions of lymphocyte populations and how populations of naive and memory cells are maintained. (iii) To develop stochastic models of T cell and B cell maturation. (iv)To develop models of autoimmunity.

Introduzione (Teaser)

The immune system protects a host organism from pathogenic microorganisms, such as viruses and bacteria. The need to develop mathematical models to explain the mechanisms that orchestrate immunological processes drove researchers around the globe to form a collaborative network.

Descrizione progetto (Article)

The immune system is inherently a complex organisation that involves many different cells and molecules. These molecular and cellular interactions dictate the potential outcome of immune responses. Thus, the use of mathematical and computational modelling in Immunology could prove extremely useful in understanding and predicting immune responses.

For a mathematical model to be successful, it needs to recapitulate the in vivo situation. This requires the incorporation of actual experimental findings and hence a close collaboration between mathematicians with experimental immunologists.

The EU-funded 'International network in theoretical immunology' (INTI) initiative aimed to support the development of such mathematical models by bringing together theoretical and experimental immunologists in one network. This would facilitate collaboration among scientists to advance mathematical modelling approaches, and sustain the exchange of knowledge among these two complementary fields of study.

From a scientific point of view, the scope of the network encompassed a variety of immune system processes, such as antigen recognition, T cell activation and T cell differentiation. Different models were formulated to explain antigen recognition and T cell receptor-ligand interactions. To avoid immune responses against self-antigens, the interaction between receptor and ligand must be highly specific and sensitive. This information was taken into account when designing models capable of explaining the affinity threshold hypothesis.

Additionally, the network generated mathematical models that can account for the fine balance between lymphocyte proliferation and death, a key process for homeostasis of T cell populations. Also considerable effort was put into models that can explain the fate of lymphocyte proliferation and the differentiation into either effector or memory cells. A theoretical model in this respect could help understand both the genetic programming component and the influence of the extra-cellular molecular environment on the interactions among cells that underlie such fate decisions.

With respect to cell-to-cell interactions, time-lapse microscopy helped visualise the process for a limited time only. Mathematical modelling helped predict the interaction for extended time frames, especially among antigen-presenting cells and T cells.

The INTI network successfully managed to bring together experimental and theoretical immunologists towards the development of new mathematical models for studying immunology. In the long run, this collaboration could lead to the establishment of large-scale models of the immune system.