1 simulation of immune system answering questions on the natural immune system behavior by...

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Simulation of Immune System

Answering Questions on the Natural Immune System Behavior

by Simulations

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INTRODUCTION

• Three questions : Q1: Is the immune innate system able to solve

all attacks? Q2: What is the actual role of the adaptive part?

Is it to improve immune reaction that can be resolved by innate part? Is it to defend against attacks unresolved by innate part?

Q3: Quantitative aspect of the intervention of each part.

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INTRODUCTION

I. Simulator Choice

CImmSim

II. Simulator Description

II.A The Computational Model

II.B The Entity Description

II.C The interactions

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INTRODUCTION

III. Simulator Behavior

III.A Basic Step of Algorithms

III.B The interaction Model

III.C The Mutation

IV. The usefulness of CImmSim for Us

V. Illustration of the Simulator Use

CONCLUSION

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I. SIMULATOR CHOICE

• SIMMUNE : only immune adaptive system simulated behavior of the cells can be defined with

flexibility copy will be available after code update

• SIMISYS : not finished project

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I. SIMULATOR CHOICE

• SIS-I,SIS-II : only T and B cells simulated

• IMMSIM: adaptive part with humoral and cellular

mediated response source code available directly (CImmSim) Cellular Automaton (CA) based

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II. SIMULATOR DESCRIPTION

II.A The Computational Model• Lymph node is mapped onto a bi-dimensional

hexagonal lattice.

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II. SIMULATOR DESCRIPTION

II.A The Computational Model• The hexagonal lattice coordinate system.

(x,y) = (u+v*sin(pi/6),u*cos(pi/6))

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II. SIMULATOR DESCRIPTION

II.B The Entity Description

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II. SIMULATOR DESCRIPTION

II.B The Entity Description

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II. SIMULATOR DESCRIPTION

II.C The Interactions• External interactions occur among cells whichhave the same position on the lattice.

v(d) is affinity potential, d is the Hamming distance, h is the affinity enhance.

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II. SIMULATOR DESCRIPTION

II.C The Interactions• The Hamming distance is the number of

complementary bits between two bit string.

In this case, the Hamming distance is the length string, i.e d=16.

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II. SIMULATOR DESCRIPTION

II.C The Interactions• External interactions occur among cells and

molecules which have the same position on the lattice.

• Internal interactions inside a cell. (MHC-Ag peptide interactions).

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III. SIMULATOR BEHAVIOR

III.A Basic Step of Algorithm• All the feasible interactions among cells and

molecules take place within a lattice site in a single time step.

• Diffusion of entities is done at the beginning of each time step.

• Time step = mitosis cycle = 8 hours.

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III. SIMULATOR BEHAVIOR

III.B The Interaction Model

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III. SIMULATOR BEHAVIOR

III.C The Mutation• In the natural human system, the normal

mutation rate is low.• In very restricted region of B cells

chromosomes, high rate of mutation occurs: the somatic hypermutation.

• The somatic hypermutation allows to obtain a collection of B cells whose receptors are better to recognize an antigen : affinity maturation

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III. SIMULATOR BEHAVIOR

III.C The Mutation• In CImmSim, we can set a parameter which

allow to enhance the affinity to the antigen only by hypermutation (see later).

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IV. THE USEFULNESS OF CIMMSIM FOR US.

• CImmSim does not implement the innate system.

• CImmSim simulates well the adaptive system.

• We can look at the time taken to clear the pathogen.

• We can learn, reuse, improve the model in order to extend the simulator such as be able to simulate the innate and the adaptive part together.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The EP cells are killed by Tk cells.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The EP cells are killed by Tk cells.

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Th and B cells interactions

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Th and B cells interactions

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The minmatch parameter.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The minmatch parameter.

• !! Drawbacks!!

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The Hole parameter.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The Bystander parameter.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The Bystander parameter.

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V. ILLUSTRATION OF THE SIMULATOR USE.

• The Bystander parameter.

• Drawback : to much of useless cells

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CONCLUSION

• The distribution in the time of the project: 2/7 used for choosing the simulator 3/7 used to full understand the model and the

simulator behavior 2/7 used for visualization and the experiments

• Skills exercised: theoretical comprehension code comprehension link between both

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CONCLUSION

• We can use the well-modeled adaptive system to see the impact of some parameters.

• We can also retain the model used to simulate the adaptive part, the interactions system, thanks to the concept of entities and cellular automaton.

• Visualization is very important. We have to know also where are the molecules and to see the space dependences between entities.

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CONCLUSION

• Future works would be to model a immune system simulator able to highlight the manner of the innate system interacts with the adaptive system using the feature of CImmSim.

• We can add entities of innate part, create new interactions between these new entities and the old one.

• We can create new states for the adaptive cells, like a “Waiting” state during which the lymphocytes wait the innate part signal.

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CONCLUSION

• We have to add new entities as self entities but not implicated in the immune process in order to check if the system simulated is dangerous for self entities.

• Again, visualization is important! We have to be able to trace all the entities : cells of the both system and molecules (have a structure to record the molecule position) and see how they interact.

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CONCLUSION

• We have to be able to see the cytokines secretion between cells which is not possible only with graph.

• We have to be able to set the influence of each cell in order to have quantitative aspect of the intervention of each part.