Transformative R01 Program

QUANTITATIVE IMAGING OF SIGNALING NETWORKS

QUANTITATIVE IMAGING OF SIGNALING NETWORKS

The rendering contains three graphical components that illustrate the combination of techniques to be developed by this transformative research project. The first component shows a snapshot of a live cell movie, where the cell expresses a fluorescent biosensor that reports in real-time the activation of a certain signaling molecule. Warm colors indicate high activation, blue colors indicate low activation. The cell area is overlaid by a meshwork to indicate that the signal activation will be recorded simultaneously for many small regions of the cell in order to allow the analysis of spatial differences. From the distribution of the colors one can see that different regions in the cell have completely different signal activation. The second graphical component shows a cartoon display of a signaling network. Arrows connect nodes to indicate the flow of information through the network. Importantly, some arrows point backwards to upstream nodes to indicate that signal transduction networks in cells involve feedback loops. It is a central goal of this research project to identify such feedbacks. Three of the nodes in the illustrated network are highlighted as bigger spheres in the colors yellow, blue, and red. This is to illustrate that while it will be impossible to measure the activation of all nodes, the goal will be to measure by live cell imaging the activation select signaling molecules in critical nodes. The third graphical component displays for each of the three measured nodes an activation sequence as it will be extracted from live cell movies. The abscissa indicates the time points; the ordinate indicates the strength of signal activation at these time points. The signal strength fluctuates in a seemingly random fashion; but since the three nodes are directly and indirectly connected in the network, the fluctuations have common motifs. New computational methods will be implemented to find the common motifs and to infer from their relationships the flow and timing of information transfer through the signal transduction network..