The European Union (EU)-funded project SYBILLA has shown how it is possible to simulate the T-cell response to different factors through an online platform, making it easier to predict the best treatments for various diseases and potentially avoiding autoimmune attacks.

The project team has produced an interactive platform to demonstrate what happens when T-cells decide to trigger an immune response against foreign substances. The activation is a complex process relying on multiple layers of tightly controlled intracellular signalling molecules, which form an intricate and dynamic network. The system allows researchers to test different combinations of factors and inhibitors to the immune system functioning, discovering more about the operations of the T-cell.

Wolfgang Schamel is SYBILLA’s project coordinator and a professor at the Faculty of Biology, the Centre for Biological Signalling Studies BIOSS and Centre of Chronic Immunodeficiency CCI at the University of Freiburg in Germany. He explains how the system simulates the signalling pathways in the cell, thus helping researchers develop new therapeutic approaches for cancer, autoimmune diseases, allergies and infections. Schamel elaborates by saying, “to really understand the immune system, one must know the molecular processes that govern activation of the immune cells by mathematics. It requires expertise from different disciplines, such as immunology, biochemistry, informatics, and mathematics – which is what SYBILLA does.”

Schamel says autoimmune diseases and allergies are increasing in the West and effective cures are often missing. SYBILLA project offers a valuable tool for immunologists and biochemists to try novel treatments. “SYBILLA has contributed to the understanding of how immune cells are activated. And indeed we now have good models to explain how these cells can distinguish foreign/harmful from self/harmless substances,” he says.

SYBILLA, a team of 17 science and industry partners, created a publicly-available online platform allowing researchers to click through the signalling network of the T cells. Users can switch on 12 receptors (including the T-cell receptor), identify the signals on the surface of other cells, or bind messengers. Taking account of the 403 elements in the system, the model then computes the behaviour of the network. The result is a combination of the activity of 52 output proteins that predict what will happen with the cell.

This could help researchers find weak points for active substances that could then be used to treat immune diseases or cancer by switching on and off particular signals in the model. ”We have uncovered molecular mechanisms with which the immune system discriminates between the healthy native cells and foreign cells, such as bacteria. Further, we have found a large number of new genes that are involved in immune cells functions and have done experiments to discover their functions. Some of them might turn out to be ideal drug targets in the future,” he adds.