Research Report 2010 2011 - Helmholtz-Zentrum für ...

116 SCIENTIFIC REPORTS | Infection and Immunity | New Project Groups
02 Systems Immunology
PROJECT LEADER | Prof. Dr. Michael Meyer-Hermann | Department of Systems Immunology | mmh10@helmholtz-hzi.de
PROJECT MEMBERS | Dr. Marc Thilo Figge | Dr. Valerii Sukhorukov | Dr. Arndt Telschow | Sebastian Binder |
Jaber Dehghany | Harald Kempf
Systems Immunology What is Systems Biology and why do
we need it? It is not possible to understand the functionality
of a system by just knowing its constituents, as derived from
„omics“-approaches. The major question is how all these
constituents interact with each other and how they give rise
to a meaningful and functional concept like an organism.
The key to this question is the dynamics of the system under
investigation. Systems Immunology is the science of developing
mathematical models of the dynamic behaviour and
interaction of complex systems related to health. The future
of research in Biology will rely on the iterative discussion of
theoretical prediction and experimental result, inspired by
the success of Physics.
of GC. We tested in silico with the aforementioned model
how disruption of TLR4-signalling would change the GC
and predicted that the mutation rate has to be reduced. This
prediction was confirmed in experiment. [3]
Directions The novel department Systems Immunology
at the HZI will work on models of dynamic systems in the
immune system and in the field of infection and inflammation.
In the coming year pre-established research fields, like
modelling of adaptive immune responses and of pancreatic
betacells in the context of diabetes, will be continued and it
is planned to develop new collaborations, in particular, with
emphasis on chronic inflammatory diseases.
Methodology As it is impossible to understand the mechanisms
of a biological system from the knowledge of its
constituents alone, we are restricted to start from phenomenological
descriptions of the whole system. These should
be as simple as possible and as complex as needed to allow
comparison with available experimental data. In an iterative
optimisation process the model assumptions are evolved up
to the point that the in silico model behaves as the in vivo
model. If theory and experiment disagree, research may take
advantage of Systems Immunology: Either the model has to
be extended or an assumption in the model has to be reconsidered.
In both cases the knowledge of how the biological
system works is improved.
The advantage of such a phenomenological approach is that
at any level of mathematical description reached so far, the
in silico model remains functional. Ultimately this approach
based on an increasingly complex picture of the biological
system will enable to (i) design new experiments that are
conclusive for specific questions, (ii) predict the outcome of
planned experiments in order to verify the consistency of the
current knowledge, and (iii) predict optimal treatment strategies
in deregulated systems.
Example generation of specific antibodies The immune
system contains a specific environment, the germinal centre
(GC), in which B lymphocytes (BC) are induced to mutate
their antibody encoding genes. Subsequently, mutated BC
undergo a selection process in order to either produce highaffinity
antibodies or to contribute to the immune memory.
The general conviction was that selection is controlled by
the availability of antigen. We have developed a mathematical
model for the GC dynamics and predicted that it is not
the antigen but affinity dependent TC help that is limiting
[1]. This prediction was verified in a series of experiments
[2] and, thus, a new concept of the GC reaction was induced.
Also toll-like-receptor-4 (TLR4) impacts on the development
In silico agent-based simulation of a germinal centre reaction.
A 20 micron thick slice of the germinal centre at day 5 after
onset of proliferation. Every object represents a cell: Dividing
and mutating BC (blue), non-dividing Ig-expressing BC (dark
green), BC with positive signals from FDC (light green), plasma
cells (white), T follicular helper cells (red), FDC (yellow)
where dendrites are not shown. The cells interact according
rules derived from present knowledge and move in response
to chemokines (not shown) and in agreement with recent intravital
two-photon imaging data. Previously published in [4].
[1] Meyer-Hermann, M., Figge, M.T., & Toellner, K.M. (2009) Trends in Immunology 30, 157-164.
[2] Victora, G.D., Schwickert, T.A., Fooksman, D.R., Meyer-Hermann, M., Dustin, M.L., &
Nussenzweig, M.C. (2010) Cell 143, 592-605.
[3] Garin1, A., Meyer-Hermann1, M., Contie, M., Figge, M.T., Buatois, V., Gunzer, M., Toellner,
K.-M., Elson, G., & Kosco-Vilbois, M.H. (2010) Immunity 33, 84-95. 1: shared first author.
[4] Figge, M.T., Garin, A., Gunzer, M., Kosco-Vilbois, M., Toellner, K.-M., & Meyer-Hermann,
M. (2008). Journal of Experimental Medicine 205, 3019-3029.