Quantifying transcription factor search mechanism by three dimensional single mo...
Quantifying transcription factor search mechanism by three dimensional single molecule tracking
Transcription factors (TFs) are capable to identify their target sites on DNA in a extremely efficient fashion. The observation that a simple 3D diffusion search cannot account for such efficient targeting has led to different me...
Transcription factors (TFs) are capable to identify their target sites on DNA in a extremely efficient fashion. The observation that a simple 3D diffusion search cannot account for such efficient targeting has led to different mechanisms to be proposed in the last decades, including compact exploration induced by facilitated diffusion (i.e. combination of 1D sliding and 3D diffusion) or by fractal-like chromatin structure. Despite the evidence for 1D sliding of TFs on DNA and for fractal nuclear organization, it still needs to be demonstrated that these phenomena play a significant role in the TF search mechanism in a living cell. Fluorescence microscopy and in particular single molecule tracking (SMT) provides an excellent tool to investigate the kinetics of proteins in living samples. SMT has mostly been applied to in-vitro and in-membrane environments due to limitations associated to prolonged 3D tracking. In this project we plan to overcome the limitations associated to 3D SMT and to apply the developed technology to investigate the in-vivo search mechanisms of p53, an important TF, involved in the determination of the cell fate under stress conditions. We aim to quantify the role of compact exploration in p53 targeting in living cells, and by the analysis of mutated p53 how 1D sliding affects such phenomenon. Furthermore, we plan to identify the changes in the p53-DNA association and in the p53 search after induction of cell stress by DNA damage. Summarizing, the project aims to strongly improve current methods for tracking individual molecules in 3D and to advance our knowledge about the mechanisms of TF targeting.ver más
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