Utrecht Center for Quantitative Immunology

Towards a more Quantitative Picture of the Immune System.....

The immune system is a fascinating complex system. It takes decisions on how to respond to harmful co-evolving pathogens, and to harmless self and food antigens. Since the immune system is composed of a large variety of circulating cell types, with cells communicating via a vast array of signaling molecules, these decisions are taken in a distributed manner. Individual circulating cells tend to remember their decisions and thereby contribute to life long immunological memory. Pathogens evolve much faster than their hosts. They evolve immune escapes by mutating their epitopes, and cheat by interfering with antigen presentation and by inducing inappropriate immune responses.

The proper understanding of such a complex system requires quantification. Fortunately, immunologists nowadays generate large, quantitative, and temporal data sets on the development of immune responses, the maintenance of memory, the lymphocyte repertoire, and the sequence evolution of the pathogens. The interpretation of these large data sets requires both bioinformatics and modeling (i.e., Systems Immunology). The Utrecht Center for Quantitative Immunology (UCQI) brings together an experienced collaborative team of immunologists, bioinformaticians, and mathematical modelers. Having worked together on quantitative immunology for more than a decade, we have learned to speak each others language, which enables fruitful iterations between our experiments and computational analysis of the immunological data generated by these experiments using modeling and bioinformatics.

We have expertise in bioinformatics, with a long history in the data-driven peptide MHC prediction tools. These tools are used to predict immune responses, study viral evolution, and answer questions about the cross-reactivity of MHC molecules and T cell receptors. We have expertise in estimating the turnover rates of the cells, their migration rates, the rates at which individual cells form contacts with other cells, and the rates at which immune cells clear pathogens upon such a contact. As a team we perform experiments in mice and man, two photon microscopy, and develop bioinformatic tools, mathematical models, and computer simulations models.

One of our model pathogens is HIV-1, which is modifying the normal population dynamics in the immune system in such a way that the system slowly collapses, and for which an enormous amount of bioinformatic data is available.

For contact information please see the pages of the individual members.