Our long-term goal is to understand how the dynamic behavior of biological signals is controlled and how these dynamics affect cellular responses. This proposal focuses on fundamental cellular mechanisms of the p53 signaling pathway. We recently used long-term time-lapse imaging studies on single cells and discovered that p53 levels show a highly unexpected pulsatile response to specific types of DNA damage. These repeated pulses had been masked in previous studies that measured p53 levels in populations of cells. We will combine quantitative dynamic measurements in single living cells, mathematical modeling and manipulation of the p53 circuit to ask how, and why, the p53 signaling pathway generates this series of uniform pulses and why different cells show different numbers of pulses.
Our first aim i s to identify the molecular mechanism leading to p53 pulses and the feedbacks that control their amplitude and duration. We will perform quantitative population and single cell measurements of the dynamics of several proteins in the p53 pathway and integrate the information into a theoretical framework, with the goal of developing a credible predictive model for p53 dynamics. Next, we will determine how p53 pulsatile behavior is connected with specific cellular outcomes and with the activation of specific downstream programs such as apoptosis, cell cycle arrest and DNA repair. We will track p53 dynamics in parallel with marker proteins that report on downstream programs in single living cells, and identify the fate of each imaged cell. We will manipulate the control circuit to alter the frequency or amplitude of the pulses, or eliminate them altogether, and ask how these changes affect the outcome for the cell. As well as asking how p53 dynamics determine outcome, we will examine whether the amount of DNA damage affects the number of pulses. We have developed a novel system for quantitating DNA double- stranded breaks (DSBs) and cell cycle stage in live cells and we will use this system in parallel with tracking p53 pulses to ask whether the initial number of DSBs affects the number of p53 pulses, and whether the cell's sensitivity to radiation changes during the cell cycle. Finally, we will determine how estrogen influences p53 dynamics and cell fate following DNA damage in cells that carry a specific polymorphism in Mdm2 promoter (SNP309), which were shown to have high levels of Mdm2 and no p53 pulses. We will predict and test the effect of estrogen antagonists and p53/Mdm2 inhibitors on p53 dynamics in the background of SNP309 cells. Our results will provide new insights into the control and manipulation of the p53 pathway, perhaps the most important pathway protecting human cells against the development of cancer. These studies will give a deeper understanding of the biological mechanisms and function of p53, and will provide a prototype for the analysis, description, and understanding of the dynamics of other signaling pathways in single living human cells.
|Reyes, José; Lahav, Galit (2018) Leveraging and coping with uncertainty in the response of individual cells to therapy. Curr Opin Biotechnol 51:109-115|
|Arbelle, Assaf; Reyes, Jose; Chen, Jia-Yun et al. (2018) A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos. Med Image Anal 47:140-152|
|Stewart-Ornstein, Jacob; Cheng, Ho Wa Jacky; Lahav, Galit (2017) Conservation and Divergence of p53 Oscillation Dynamics across Species. Cell Syst 5:410-417.e4|
|Stewart-Ornstein, Jacob; Lahav, Galit (2017) Integrating genomic information and signaling dynamics for efficient cancer therapy. Curr Opin Syst Biol 1:38-43|
|Oppenheim, Ariella; Lahav, Galit (2017) The puzzling interplay between p53 and Sp1. Aging (Albany NY) 9:1355-1356|
|Hafner, Antonina; Stewart-Ornstein, Jacob; Purvis, Jeremy E et al. (2017) p53 pulses lead to distinct patterns of gene expression albeit similar DNA-binding dynamics. Nat Struct Mol Biol 24:840-847|
|Stewart-Ornstein, Jacob; Lahav, Galit (2017) p53 dynamics in response to DNA damage vary across cell lines and are shaped by efficiency of DNA repair and activity of the kinase ATM. Sci Signal 10:|
|Chen, Sheng-Hong; Lahav, Galit (2016) Two is better than one; toward a rational design of combinatorial therapy. Curr Opin Struct Biol 41:145-150|
|Stewart-Ornstein, Jacob; Lahav, Galit (2016) Dynamics of CDKN1A in Single Cells Defined by an Endogenous Fluorescent Tagging Toolkit. Cell Rep 14:1800-1811|
|Chen, Sheng-Hong; Forrester, William; Lahav, Galit (2016) Schedule-dependent interaction between anticancer treatments. Science 351:1204-8|
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