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Integrated cell and tissue models


One of the innovative competences is the design of "computational tissues" that will allow to study the functional and the morphological changes of tissues, taking into account molecular, biochemical, and biomechanical data. A major objective of this approach is to achieve a fundamental systemic understanding of the spatio-temporal processes involved in tissue formation and functioning. A major challenge is to generate validated in silico tissue models that can directly be compared with experiments (modelling, tissue organization, multicellular systems).


Comparision of in vitro and in silico colony growth.
A) Vertical section through an in silico cell population. Blue: cells with substrate contact, green: cells without contact. Colour saturation (arrow heads) indicates cell division.
B) Top view on two cultured populations stained for proliferation by BrdU, growing from cells of different subpopulations (SPfast, SPslow).
C) Simulation results related to B).
D) Cell number per colony versus time.
E) Diameter of colonies shown in D) Lines are simulation results.

Modelling developmental or regenerative systems requires considering the regeneration potential of tissue stem cells. A common paradigm explaining the self-renewal of tissue stem cells is the concept of a unidirectional differentiation hierarchy, which treats "stemness" as an explicit cellular property. However, experimental findings have indicated that the cell development is far less determined than usually believed. These results led us to re-design the tissue stem cell concept. A group at the IMISE introduced a new model paradigm: the assumption of a "phenotypic reversibility" of stem cells (DYNAMO). It provides the framework for a novel class of 3D individual cell-based tissue models (Tissue Organisation). However, to be able to successfully use stem and progenitor cells in regenerative medicine and drug-screening approaches, a comprehensive and systemic understanding of the regulatory processes governing lineage specification, differentiation and cellular fate determination is inevitably required. Such investigations are strongly related to the exploitation of information originated by genome, proteome, and toponome analysis and the understanding of functional directed molecular mechanisms.
Strong interdisciplinary groups (IZBI, IMISE, MPI) have been formed, working on models in the fields of haematopoietic feedback regulation, tissue stem cell organisation, models of regenerating epithelial tissues (cp. publications), and models of retinal histogenesis. They are supported by a network of experimental groups combining a broad spectrum of complementary approaches relevant to the quantitative visual and functional analysis of cells and tissues(cp. DMPT, http://www.uni-leipzig.de/~bader/).


A) Traditional and recently proposed view on stem cell (SC) differentiation and lineage specification. In contrast to the classical concept that assumes differentiation to be a unidirectional stepwise process, recently proposed concepts suggest to understand differentiation as a continuous and reversible process. Model of an intestinal crypt considering phenotypic reversibility. Proliferating cells (blue) emerge at the bottom of the crypt and migrate out. During that process they differentiate (green). Mature enterocytes are shed into the intestinal lumen. The differentiation of the cells is assumed to be reversibly triggered by the heterogeneous composition of the basal membrane (polymer network: red, crosslinks: green).

PDF-versions of publications are available at: IMISE

Engel C, Scholz M, Loeffler M. A computational model of human granulopoiesis to simulate the hematotoxic effects of multicycle polychemotherapy. Blood. 2004;104(8):2323-31.
Galle, J., M. Loeffler and D. Drasdo. 2005. Modelling the effect of deregulated proliferation and apoptosis on the growth dynamics of epithelial cell populations in vitro. Biophys J. 2005; 88(1): 62-75.
Loeffler M, Roeder I. Tissue stem cells: definition, plasticity, heterogeneity, self-organisation and models--a conceptual approach. Cells Tissues Organs. 2002; 171(1):8-26.
Missal K, Cross MA, Drasdo D. Gene network inference from incomplete expression data: transcriptional control of hematopoietic commitment. Bioinformatics. 2006; 22(6):731-8.
Roeder I, Glauche I. Towards an understanding of lineage specification in hematopoietic stem cells, J. Theor. Biol., doi: 10.1016/j.jtbi.2006.01.021
Roeder I, ...Loeffler M. Competitive clonal hematopoiesis in mouse chimeras explained by a stochastic model of stem cell organisation, Blood 2005, 105(2):609-16.
Scholz M, Engel C, Loeffler M. Model-based design of chemotherapeutic regimens that account for heterogeneity in leucopoenia Br. J. Haematol. 2006. 132(6), 723-735.