Immune System Modelling and Simulation

The book describes a computational model of the immune system reaction, C-ImmSim, built along the lines of the computer model known as the Celada-Seiden model (CS-model). The computational counterpart of the CS-model is called IMMSIM which stands for IMMune system SIMulator. IMMSIM was written in 1992 by the physicist Phil E. Seiden and the immunologist Franco Celada. This model was built around the idea of developing a computerized system to perform experiments similar in vivo experiments; a tool developed to help biologists testing theories and hypothesis about how the immune system works. C-ImmSim is best viewed as a collection of models in a single program. It incorporates the principal core facts of today’s immunological knowledge, such as the diversity of specific elements, MHC restriction, clonal selection, thymic education of T cells, antigen processing and presentation (both the cytosolic and endocytic pathways are implemented), cell-cell cooperation, homeostasis of cells created by the bone marrow, hyper mutation of antibodies, maturation of the cellular and humoral response, and memory. Besides, an antigen can represent a bacterium, a virus, or an allergen or a tumor cell. C-ImmSim has been recently customized to simulate the HIV-1 infection. Moreover, it can simulate the immunotherapy for cancer. These features are all present in the code and people can choose to turn them on and off at compiling time. The book presents the basic model as well as the various customizations to implement the description of different diseases and the way they have been used in practice to produce new knowledge either from hypothesis or from lab-experiment data. In this respect, the book can be used as a practical guide to implement a computational model with which to study a specific disease and to try to address realistic clinical questions.

Immunology for aliens Leo Szilard paradox: Grand Central Terminal Non-specific defense Levels of evolution How is a trait selected if it was not needed? Luck or foresight? Blood brothers The members of the winning team are rewarded Somatic recombination produces diversity among equals The workshop of the adaptive response Repertoires A battalion of one Self-inflicted damage threatens survival Don’t think, but reason and understand Full cover comes at a cost A bet, not a fantasy, about earliest happenings The cooperation of very different cells multiplies jobs that can be done Thymus deeds Hypothesis is a bet: Tips for the Aliens To grow and to change Philosophy storm Suicide In the beginning The linear transmission of activation Recipe for complete Freund have them An antibody is an antibody (or two?) Scientific Myths: God's mess with human cognition A monument to interdisciplinarity Scientific Myths 2: Apollo roams about the hills of Tennessee Plain reasoning breaks the Spell Of wolfs, dogs and shepherds How to block anti-self Controlling self- damage needs structures: the lymphoid organs Time of strengthening Maturity A cognitive system? A floating brain? Cellular Automaton makes sense Memory is in the numbers The power rests with whoever issues regulatory signals The seed is prepared during the primary response The challenge Competition in the minefield of cross reactions The compensated immune system wants to understand The two immune systems The cellular branch confronts a virus infection How to model the cellular and the humoral together Body and soul, actions and philosophy What steps can and should be simulated Attrition and cross-reaction Memory is strong, sometimes too strong IMMSIM reveals MaN (Memory anti Naïve) as a cause of aging A course leading to aging of the immune system A new challenge for modelers: conformation Protein Conformation and the immune system Antibody mediated activation of a mutant enzyme More fields for models, and where to find them A note to encourage cross referencing An unconventional glossary for aliens Aliens for immunology The unusual mix of immunology and computer science Classical modeling techniques versus the "new kind of science" From spin-like to agent-based models The ancestors The others C-ImmSim unveiled Model compartments The cells The molecules The repertoire The molecular affinity Reshaping the affinity landscape Haematopoiesis and cell homeostasis The selection of cells in the thymus The Hayflick limit Cell aging and death A (dynamic) immune memory The hyper-mutation of antibodies Immune activation Anergy Interactions among entities Antigen digestion and presentation Cell motion and diffusion of molecules Main procedures Notes on the expressed repertoire Scaling the system size Few words on the definition of molecular quanta The choice of the MHC molecules The parameters What to monitor? Benchmarks aka qualitative model validation Primary and secondary response Exhaustion Bacterial Infection Viral infection Modelling idiotypes and the idiotype network Specific applications A multi-scale approach to model hypersensitivity HIV infection and AIDS Immunodominance in cancer immunotherapies Embedding immunoinformatics predictions One last word Bibliography

Filippo Castiglione, Franco Celada