Fluorescence imaging of signaling networks

Abstract

Receptor-triggered signaling processes exhibit complex cross-talk and feedback interactions, with many signaling proteins and second messengers acting locally within the cell. The flow of information in this inputoutput system can only be understood by tracking where and when local signaling activities are induced. Systematic strategies are therefore needed to measure the localization and translocation of all signaling proteins, and to develop fluorescent biosensors that can track local signaling activities in individual cells. Such a biosensor tool chest can be based on two types of green fluorescent protein constructs that either translocate or undergo fluorescence-resonance-energy transfer when local signaling occurs. Broad strategies to measure quantitative, dynamic parameters in signaling networks, together with perturbation approaches, are needed to develop comprehensive models of signaling networks * .Recent technical developments have made it possible to ask how information flows from many different cellularreceptor inputs to a diverse set of physiological cell functions (outputs). Expression profiling [1], proteomics [2] and evolutionary comparison with known signaling proteins [3] can now be used to identify all predicted signaling proteins in a particular cell type. Although studies in yeast and other model organisms have been leading the way, these approaches can now be applied to obtain a list of relevant signaling proteins in a particular mouse or human cell. Given our current knowledge, one can expect a typical mammalian cell to contain somewhere between several hundred and a few thousand different signaling proteins, and more than ten second messengers. These signaling proteins and second messengers are organized in a network-like fashion, and it is likely that some of the principles of metabolic networks [4] and transcriptional networks [5,6] also apply to mammalian signaling networks.To discuss some of the unique features of the cell signaling problem, an idealized signaling network is shown in Fig. 1. As a working hypothesis, the internal structure of this input -output system can be described using three concepts: signaling pathways, signaling modules and signaling nodes. For signaling pathways, the main flow of information is sequential and goes through a linear chain of intermediate steps from the receptor to a particular cell function. This idea has been extremely powerful and has shaped our current view of signal transduction. For example, tyrosine kinase and other receptor stimuli turn on a multistep mitogenactivated-protein-kinase pathway to activate specific genes that upregulate cell growth [7].The second concept of signaling modules can be subdivided into modules that are connected by feedback involving a diffusion step (diffusible feedback systems) and modules that are physically linked complexes of signaling proteins and/or scaffolding proteins [8,9]. An example of a diffusible feedback module can be seen in the positive and negative feedback loops by which calcium and the inositol...

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