Understanding T Cell Activation: Mechanisms in Health and Disease
This study explores the intricate mechanisms underlying T cell activation, focusing on the duality of recognizing and eliminating infected cells while ignoring healthy self-tissues. It addresses the role of MHC affinity in determining T cell outcomes, with high-affinity signals leading to activation and low-affinity signals supporting survival. The research is part of the EU-funded SYBILLA project, bringing together international partners to advance understanding of T cell dynamics. Insights aim to elucidate the foundations of autoimmune diseases and persistent infections.
Understanding T Cell Activation: Mechanisms in Health and Disease
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Presentation Transcript
Wolfgang Schamel Systems Biology of T Cell Activation in Health and Disease:
T-cell activation: • recognize and eliminate infected cells (foreign peptides) • ignore healthy self-tissues, although they are recognized (self-peptides) How is this discrimination achieved ?
T-cell activation: • recognize and eliminate infected cells (foreign peptides) -> severe, persistent infections • ignore healthy self-tissues, although they are recognized (self-peptides) -> autoimmune diseases How is this discrimination achieved ?
The affinity of MHCp determines the T cell stimulation outcome. T cell high affinity activation TCR MHCp 1 low affinity survival TCR MHCp 2 Nature 2006, Ed Palmer, CH partner of SYBILLA
The affinity of MHCp determines whether an autoimmune disease develops. T cell presenting cell high affinity disease TCR MHCp 1 low affinity no disease TCR MHCp 2 Nature 2006, Lars Fugger, UK partner of SYBILLA
-> what is the difference between signal A and signal B ? high affinity peptides (foreign) signal A activation of T cell low affinity peptides (self) signal B survival of T cell
PLoS Comp. Biol. 2007, Burkhart Schraven and Jon Lindquist, D partners of SYBILLA
Aim: To understand the intracellular network that governs T cell activation • SYBILLA: • EU-funded collaborative project • 17 partners (14 EU, 2 USA and 1 India) • 11.1 M Euros • 5 years (start: April 2008)
Standardized quantitative protein data using a murine T cell line : Validation projects - Primary, naive T cells - Human T cells - Multiple sclerosis model Modelling projects - Dynamic models of many modules (incl. PTM, interaction & localization data) - Correlative models (incl. transcriptomics) - Extend and dynamize the Boolean network Interactomics project - identify the interaction partners of 200 proteins of the network after stimulation with foreign and self-peptide MHC
EU FP7 proteome-based approach EU transcriptome-based approach US The Immunological Genome Project
Webpage www.SYBILLA-T-cell.de Coordinator: Wolfgang Schamel, schamel@immunbio.mpg.de
