Systems Biology for Cellular Engineering

The epidermal growth factor (EGF) receptor (EGFR) belongs to the family of receptor tyrosine kinases, also known as ErbB receptors. These receptors trigger a rich network of signaling pathways and regulate cell functions, such as proliferation, differentiation and migration, and play a key role in the genesis of many tumors. Deregulations, e.g., overexpression of Her2 (one of the members of the EGFR family), of receptor activity have been reported in various types of cancers. Therefore, a detailed understanding of the mechanisms of receptor activation is critical. The objective of our work is to understand the spatiotemporal features of the early signal sensing steps of ligand binding and receptor dimerization along with downstream functionality. We analyze the influence of the spatial heterogeneities of the membrane EGFRs on the response of signalling events by modulating EGF binding and EGFR dimerization.

The equilibrium binding of EGF on EGFR, resulting in a concave up Scatchard plot, has been an issue of debate for over a decade. We have developed a compartmental equilibrium model to represent heterogeneity in the local EGFR density. The model can explain the shape of the Scatchard plot; fitting of experimental data suggests EGFR localization is in agreement with microscopy studies.

Figure 2:Comparison of Scatchard plot from our heterogeneous receptor density model, two site model and experimental data. For more information, see K. Mayawala, D.G. Vlachos, J.S. Edwards, FEBS Letters 579, 3043-3047 (2005).

An outstanding issue is the selection of a suitable model to study the kinetics of receptor dimerization. To meet this goal, a criterion for choosing a suitable model (spatially distributed vs. well-mixed and deterministic vs. stochastic) was developed using a modified Damköhler (Da) number. Our simulations indicate that the effective reaction rate constant decreases with time due to time dependent changes in the spatial distribution of receptors. As a result, PDEs can lead to misprediction of the effective reaction rate constant by up to two orders of magnitude.

Figure 3:Evolution of intensity of dimerized receptors with two ligands (high intensity spots) and of monomer plus dimerized receptors with a single ligand bound (low intensity spots) along with the data of single particle tracking experiments of (Sako and others 2000). For more information, see K. Mayawala, D.G. Vlachos, J.S. Edwards, BMC Cell Biology 6, 41 (2005).

Figure 4:Effectiveness factor as a function of a Da number calculated at 33% of the equilibrium concentration of the dimer produced from the reversible dimerization reaction. The bottom curve is representative of an average EGFR density in typical normal cells, the middle curve of localization in normal cells and of an average EGFR density in cancer cells, and on the top curve of localization in cancer cells. The points represent the mean of 30 concentration profiles obtained from the different random number seeds. For more information, see K. Mayawala, D.G.Vlachos, J.S.Edwards, Biophysical Chemistry, Accepted (2006).

We have developed a spatially distributed, multiscale Monte Carlo based simulation framework to enable the simulation of receptor dynamics, and comparison to various microscopy techniques. The results from MC simulations are in excellent agreement with single particle tracking microscopy and biochemical data. Substantial differences in signaling between normal and cancer cells are observed due to localization.

Overall, our work suggests the existence of a layer of control at the cell surface by altering the signal sensing mechanism. Ongoing efforts to understand the importance of spatiotemporal aspects of this pathway focus on mechanisms of clustering and endocytosis, and on linking these processes to intracellular signaling.