Robust Analysis of Signal Transduction Underlying Cellular Variability in Stem Cells

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At the molecular level no cell is like any other. Differences between genetically identical cells can in fact be quite pronounced, and these differences can have profound biological and biomedical implications. Stem cells divide and differentiate in response to physiological and environmental cues but exhibit considerable differences in how they do so; equally, tumour cells respond differently to drug treatment or radiation therapy. The mechanisms driving such variability among to all intents and purposes seemingly identical cells are only poorly understood. In order to understand these fundamental processes - which also have numerous biomedical and pharmacological implications - we have to overcome experimental and mathematical modelling challenges. Here we develop the necessary experimental and theoretical frameworks, which allow us to probe single cells, measure the abundances of key signalling molecules, and infer mathematical mechanistic models for signal transduction. We will then analyze these mathematical models in order to understand better how the structure of the signal transduction network influences cell-to-cell variability. Most importantly, however, we will develop novel strategies which will allow us to guide cellular decision making processes and determine patterns of differences between cells. If we manage to reduce or otherwise affect such variability then we gain a novel way to guide the behaviour of cells.