Generalisation of a procedure for computing transcription factor profiles

Using the Tet-On system to develop a procedure for extracting transcription factor activation dynamics

The regulation of gene expression by transcription factors through different expression and activation dynamics is an important aspect of genomics and systems biology. Reporter systems using green fluorescent protein (GFP) or luciferase are often used to infer transcription factor dynamics. We recently used an inverse problem solution of GFP reporter profiles to demonstrate that the activation dynamics of a model transcription actor (NF-kappaB) can be reconstructed from GFP data. This approach assumes that the general nature of the transcription factor dynamics is known; however, it is non-trivial to determine the exact nature of the transcription factor dynamics as it often depends upon the cell type and the stimulus used to activate the transcription factor. This, in turn, limits the determination of accurate transcription factor dynamics from reporter data, especially since the model used for solution of an inverse problem needs to be verified. To address this point, we developed a reporter cell line for expressing GFP using an inducible, artificial transcription factor (tTA) and minimal promoter system. The artificial transcription factor can be activated independent of the cellular regulatory machinery through addition of doxycycline. This allows us to directly control the dynamics of the artificial transcription factor, and thereby, develop a model describing its activation dynamics from reporter data. Our experimental data and model predictions are in good agreement, and illustrate the utility of our approach. Future work will focus on using the developed approach, i.e. solution of an inverse problem involving the model describing expression of GFP, to extract the dynamics of transcription factors that are currently uncharacterized.