NSF Award
0848030
Cells are constantly bombarded with molecular signals that they must interpret in order to respond appropriately to environmental cues. Much of the cellular decision making is carried out via signaling cascades that translate the engagement of surface receptors first into altered protein phosphorylation patterns and then into gene regulation. A critical issue in this field of signal transduction is to understand how cells accurately respond to environmental cues. <br/>To address this issue, two types of cells (PC12 pheochromocytoma and T lymphocytes) will be studied in this project. For these cells, the activation of a specific signaling cascade (e.g. mitogen-associated protein kinase pathway or MAPK) is triggered upon sensing of external ligands, and this cascade results in either cellular quiescence, differentiation and/or proliferation. PC12 cells can discriminate between nerve growth factor and epidermal growth factor ligands by differentially regulating the dynamics of their signaling response. T cells detect the presence of few foreign-derived ligands while avoiding spurious activation by large quantities of self-derived ligands. In both types of cell, this ligand discrimination has been shown to be highly tunable (e.g. during neurocytic or thymic development) and at the same time reliable (despite stochastic variability among cells).<br/><br/>In this project, the PI will combine computational and experimental approaches to reconcile this robustness and variability in cell signaling. First, computer models of cell signaling will be developed to probe the theoretical robustness of ligand discrimination in the context of stochastic fluctuations in chemical reactions, and phenotypic variation (i.e. expression of different levels of signaling components). Second, the variability of signaling responses due to phenotypic variability will be monitored experimentally: alteration in cell responsiveness will be mapped onto the differential expression of key signaling components at the single cell level. The PI will also use perturbation (through chemical inhibition of kinase/phosphatase enzymes or up/down regulation of signaling components) to modulate cell responsiveness and test theoretical predictions. <br/><br/>This project is based on the PI's development of computer models of signal transduction, as well as the development of multiplexed detection of phosphorylated states in individual cells. Thus, it is a unique opportunity to merge theoretical and experimental approaches to study the systems biology of cell signaling.<br/><br/>Broader impact <br/><br/>This project addresses a fundamental paradox in signal transduction whereby PC12 cells and T lymphocytes utilize feedback regulation of MAPK activation to enforce ligand detection with functional variability yet with reliability. Understanding such feedback regulation will allow the derivation of general principles at the systems biology level to explain how signaling networks can reconcile robustness and variability in their input/output relationships. The project will include the training of postdoctoral, graduate and undergraduate students in systems biology, ranging from experimentation to computer modeling. Tutorials, journal clubs and discussion groups will be used to introduce students and postdoctoral fellows to systems biology. Moreover, new implementations of biochemical computer models will be broadcast to the scientific community such that other researchers can use them, edit them, and test their own hypotheses in signal transduction. Experimental data will also be deposited in repositories (e.g. DREAM3 database) to help the systems biology community test different modeling approaches.
