Our lab studies how individual cells translate internal and external signals into decisions such as growth, death, movement or differentiation. We quantitatively measure the changes in level, activity, or localization of proteins in single cells at high temporal resolution and correlate these behaviors with specific cellular fates. By visualizing how dynamical behaviors vary between different cells, we aim to tease out the reasons for varying behavior both in cell populations and in different cell types. Understanding these issues will be enormously important for understanding how drugs act on different cell types and organs, and to begin to gain insight into the reasons why different cells and people respond differently to specific drugs.

We focus on the p53 signaling pathway. p53 is the protein most frequently inactivated in human cancer; more than half of all human cancers contain mutations in the p53 gene, and in almost all cancers the p53 regulatory circuit is functionally inactivated. Earlier work on p53 dynamics used techniques that average the behavior of millions of cells together (e.g. Western blots). We are interested in examining how individual cells behave. We use live single-cell imaging system and fluorescently labeled reporter proteins to determine how p53's dynamic behavior is controlled, why different cells show different dynamical behaviors and what consequences these behaviors have on cell survival. We apply the same approaches and techniques to study additional networks in human cells such as the networks controlling DNA repair and cell growth. Some of the questions we are currently interested in include:

• How does the cell evaluate the level of its DNA damage and transfer this information to p53?
• What combination of p53 dynamics and p53 modifications triggers a given cell fate program?
• What is the dynamical behavior of wild-type and mutant p53 in response to different stresses?
• Can we ‘rewire' the p53 network to affect p53 behavior and the cell fate?

In the long term we are optimistic that these studies will help us predict how signaling networks in human cells will behave in response to new stimuli; how they can be modified or rebuilt to give a desired cellular output; and how to selectively increase the tendency for cancer cells to go in the direction of apoptosis by modulating the dynamics of the networks controlling this decision.