GROUP: Theoretical Systems Biology

We are interested in cellular decision making by signal transduction networks and at the level of gene expression. We apply different theoretical methods ranging from ODE-based mechanistic modeling, over reverse engineering algorithms to agent-based modeling of cell population behaviour.

 


The research group "Theoretical Systems Biology" is interested in cellular decision making by signal transduction networks and at the level of gene expression. We apply different theoretical methods ranging from ODE-based mechanistic modeling, over reverse engineering algorithms to agent-based modeling of cell population behaviour. Furthermore the group focusses on epigenetic mechanisms and their relevance for disease.

Epigenetic reprogramming by environmental exposure and consequence for disease risk

Epigenetic mechanisms have emerged as potential links between prenatal environmental exposure and increased disease risk later in life. Based on the unique LINA-mother-child cohort (Junge et al., 2014 Clinical Immunology; Weisse et al., 2013 Allergy), which is managed by our collaboration partners at the UFZ in Leipzig we study epigenetic changes induced by maternal environmental exposure at base pair resolution by mapping DNA methylation, histone modifications and transcription in expectant mothers and newborn children.

Based on longitudinal whole genome bisulfite sequencing we study the induction of DNA methylation changes in mothers and childen through maternal exposure or other factors such as Vitamin D levels (Junge et al., 2015 Journal of Allergy and Clinical Immunology).

We have shown that those changes are conserved over years of life and might contribute to disease risks later in life. The observed differential methylation leads to multiple, regulatory interactions with distal genes. We also observe that epigenetic deregulation is associated with an increased risk for lung disease in children.

Cellular Life/Death Decisions

Apoptosis ('self killing') allows multicellular organisms to eliminate damaged cells in order to maintain tissue homeostasis, a process often disturbed in cancer cells. Autoreactive immune cells are removed by apoptosis in order to prevent autoimmune diseases. In the immune system, apoptosis is typically initiated by stimulation with pro-death ligands such as CD95L, which in turn activate the central intracellular apoptosis executioners, known as caspases. The caspases involved in CD95L-induced apoptosis (e.g., Caspase-8) have been identified, but a quantitative understanding of spatio-temporal caspase regulation at the single-cell level is still lacking. Using western blot and single-cell caspase activation data, we are currently testing and validating a quantitative model that describes the mechanisms of Caspase-8 autoprocessing and activation in more detail than previously proposed mathematical  models

Project: Compartmentalization and cell-to-cell variability in caspase-8 activation

Caspase 8 ActivationWhile intrinsic apoptosis has its origin in intracellular impairments as DNA damage, extrinsic apoptosis is caused by the binding of cell death ligands to death receptors at the plasma membrane. After ligand binding, the intracellular adaptor protein FADD connects to cell death receptors, leading to the formation of death inducing signaling complexes (DISCs). At these complexes procaspase-8 dimerizes and is processed to caspase-8, the first active enzyme of the apoptotic program. We study the activation of caspase-8 at DISCs with mathematical models in combination with experiments. To measure caspase-8 activity in single cells we used fluorescent cleavage probes and confocal microscopy. By combining single cell and population experiments we could understand mechanistic details of this activation process and characterize the roles of relevant signaling proteins for causing cell-to-cell variability in death kinetics (Stefan Kallenberger, cooperation with Dr. Joel Beaudouin, Signal Transduction Biophysics).

 

Control over Cell Proliferation vs. Differentiation

Tumors are typically characterized by dedifferentiation and excessive cell division. Accordingly, a deregulated balance between pro- and antiproliferative signaling is considered to be one of the hallmarks of cancer cells. Using mathematical modeling, we are investigating the dynamic interplay between proliferative EGFR signaling and anti-proliferative TGFbeta signaling. In this line, we have previously established and experimentally validated data-based models of TGFbeta/Smad signaling, EGFR trafficking, MAPK signaling and MAPK-induced gene expression. In the future, we will extend these models in order to describe the regulation of downstream target genes (e.g., hepcidin regulation by TGFbeta/Smad signalling) and their modulation by microRNAs. Based on co-stimulation experiments, we will quantitatively describe complex multi-level crosstalk between TGFbeta and EGFR signaling, and will determine the molecular determinants for cellular pro-/anti-proliferation decisions.