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 probe circuits and identify important regulatory mechanisms, such as feedbacks. 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: While there has been a great deal of interest in the p53 response to gamma radiation, it is only one of numerous stresses that can activate p53, including additional forms of DNA damage, ribosomal stress, and oncogenes. We have shown that p53 shows the strikingly distinct dynamical behavior of graded pulses when exposed to UV radiation. Our preliminary studies have also found that activation of p53 by certain chemicals can generate either undamped pulses or graded pulses. 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. Identifying the different dynamical classes and the stresses that cluster in each class will provide a foundation for understanding a previously unknown level of regulation of the p53 network, and will inform research into the function of p53 dynamics. 2. Identifying target gene expression patterns based on p53 dynamics: Our discovery of p53 dynamical classes suggests that p53 target genes may show complex dynamical expression patterns that impact cellular responses. For example, it may be that certain pro-apoptotic genes are expressed in a step-wise manner when p53 undergoes gamma-type dynamics, but are expressed with fast saturation kinetics when p53 undergoes UV-type dynamics. This could be translated into differential triggering of apoptosis, which is consistent with the fact that distinct cell fates occur in response to gamma or UV radiation. Since p53 regulates over 100 genes, we will begin by taking a qPCR approach to probe the function of p53 dynamics. Validation by more detailed studies of important target genes will be performed using single-cell level analysis with fluorescent transcriptional reporters. We will analyze gene expression profiles for stimuli within individual p53 dynamical classes and across distinct classes. We predict that genes with expression patterns that are dependent on p53 dynamics will cluster by the dynamical classes. To verify the dependence of gene expression on p53 dynamics, we will compare stress-response profiles to profiles for conditions in which we have perturbed p53 dynamics. In preliminary studies, we have used small molecules, RNAi of feedback regulators, and synthetic engineered feedbacks to perturb the dynamical response to gamma or UV. PROGRESS IN FY2011: The Systems Biology Section of the NCI Laboratory of Pathology was established in May 2011 with my (Dr. Eric Batchelor) hiring. Since my arrival, I have completed the overseeing of the construction and furnishing of the physical lab and office space. I have procured the majority of the scientific equipment required to perform the experiments. The largest and most important equipment for the project, an inverted fluorescence microscope with environmental chamber for the long-term time-lapse imaging experiments, is currently still in the procurement process. It is anticipated that the arrival and installation of the microscope will occur in the first quarter of FY2012. I am currently in the process of reviewing applications and interviewing candidates for the two postdoctoral fellows and one FTE Biologist position for the Systems Biology Section. Some of the research findings from which the proposed project developed were published shortly after my arrival in Molecular Systems Biology (Batchelor E et al., Stimulus-dependent dynamics of p53 in single cells. Mol. Syst. Biol. 7: 488, 2011).

National Institute of Health (NIH)
National Cancer Institute (NCI)
Investigator-Initiated Intramural Research Projects (ZIA)
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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
Toettcher, Jared E; Mock, Caroline; Batchelor, Eric et al. (2010) A synthetic-natural hybrid oscillator in human cells. Proc Natl Acad Sci U S A 107:17047-52

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