PURPOSE: In this project, we will use a combination of computational and experimental techniques to characterize p53 dynamics in healthy and cancerous cells in response to important cellular stresses. To measure the dynamics of circuit components, we will use long-term time-lapse fluorescence microscopy of living cells. We will use chemical and genetic perturbations to alter p53 dynamics and determine the effect on p53 target gene expression and cell fate. Using computational modeling, we will integrate these data with measurements of cellular outcomes to predict pathway behavior in response to specific perturbations. By allowing us to study emergent properties that are not evident at the level of smaller-scale interactions, this type of approach will provide novel strategies for manipulating circuit functions, as well as new ways to combat cancers in which p53 dynamics are dysregulated. MATERIALS AND METHODS: 1. Determining classes of p53 dynamics based on p53 stimuli: We will determine the p53 dynamical response to a broad range of stimuli and classify stresses based on p53 dynamics. We will use long-term time-lapse fluorescence microscopy to measure the dynamics of fluorescently-tagged p53 at high temporal resolution in single cells. 2. Using synthetic biology approaches to control p53 dynamics: We will use synthetic biology approaches to perturb various characteristics of p53 dynamics (for example, p53 pulse amplitude, duration, and frequency), and determine the effect that such perturbations have on p53's downstream functions. 3. Identifying target gene expression patterns based on p53 dynamics: We will probe the function of p53 dynamics in the regulation of the over 100 p53 target genes at the single cell level. Validation by more detailed studies of important target genes will be performed using single-cell level analysis with fluorescent transcriptional reporters. PROGRESS IN FY2013: We have begun looking at a broad range of natural stimuli of p53, and have identified unique dynamical regulation of p53 in response to novel stresses. We are currently characterizing these new responses and identifying the regulatory mechanisms that generate them. We have also made progress in developing methods to manipulate p53 dynamics through the use of chemical and synthetic biology perturbations. We have also made significant progress in the use of novel technologies to quantify expression of large sets of p53 regulated genes in single cells.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Investigator-Initiated Intramural Research Projects (ZIA)
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National Cancer Institute Division of Basic Sciences
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Batchelor, Eric; Loewer, Alexander (2017) Recent progress and open challenges in modeling p53 dynamics in single cells. Curr Opin Syst Biol 3:54-59
Porter, Joshua R; Telford, William G; Batchelor, Eric (2017) Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards. J Vis Exp :
Harton, Marie D; Batchelor, Eric (2017) Determining the Limitations and Benefits of Noise in Gene Regulation and Signal Transduction through Single Cell, Microscopy-Based Analysis. J Mol Biol 429:1143-1154
Porter, Joshua R; Fisher, Brian E; Batchelor, Eric (2016) p53 Pulses Diversify Target Gene Expression Dynamics in an mRNA Half-Life-Dependent Manner and Delineate Co-regulated Target Gene Subnetworks. Cell Syst 2:272-82
Porter, Joshua R; Batchelor, Eric (2015) Using computational modeling and experimental synthetic perturbations to probe biological circuits. Methods Mol Biol 1244:259-76
Batchelor, Eric; Kann, Maricel G; Przytycka, Teresa M et al. (2013) Modeling cell heterogeneity: from single-cell variations to mixed cells. Pac Symp Biocomput :445-50
Moody, Amie D; Batchelor, Eric (2013) Promoter decoding of transcription factor dynamics. Mol Syst Biol 9:703
Purvis, Jeremy E; Karhohs, Kyle W; Mock, Caroline et al. (2012) p53 dynamics control cell fate. Science 336:1440-4
Batchelor, Eric; Loewer, Alexander; Mock, Caroline et al. (2011) Stimulus-dependent dynamics of p53 in single cells. Mol Syst Biol 7:488
Geva-Zatorsky, Naama; Dekel, Erez; Batchelor, Eric et al. (2010) Fourier analysis and systems identification of the p53 feedback loop. Proc Natl Acad Sci U S A 107:13550-5

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