Eric Batchelor, Ph.D.
Laboratory of Cell Biology
Building 10, Room B1B42
Bethesda, MD 20892-1500
To survive, cells must accurately detect intracellular and extracellular conditions and produce appropriate responses. These responses are determined by a complex network of interactions, including protein-protein interactions, transcriptional regulation, and mRNA processing. Over the past several decades, a great deal of progress has been made in identifying the specific biomolecules of the network, as well as the interactions between the biomolecules.
The next challenge is to understand how the complex dynamical interactions of the network are regulated, and how this regulation contributes to proper cellular function. This level of understanding often requires a multi-disciplinary approach, drawing upon techniques from biology, chemistry, mathematics, physics, and computer science to analyze quantitatively the biological "circuits" within the network. Ultimately, tackling this challenge not only is important for understanding the proper functioning of a cell, but also will likely provide novel therapeutic strategies for disease states in which the cellular network is dysregulated.
In our lab, we focus on quantitatively understanding the regulation and function of mammalian stress responses. These responses are important for a wide range of biological processes, including the responses to DNA damage and oncogene activation. We employ a variety of approaches to analyze stress response circuits:
- We use long-term time-lapse fluorescence microscopy to quantitatively measure dynamical changes in the concentration, localization, and activity of biological circuit components. These measurements are made at the single-cell level, which provides a wealth of information not observable from traditional measurement methods that rely on population averaging of data.
- We use synthetic biology approaches to perturb biological circuits, such as interfering with existing network connections using small molecule inhibitors or RNAi, or creating new circuit feedbacks and feed-forwards through genetic perturbations.
- We complement our experimental studies with computational modeling of biological circuits. These models enable us to more formally synthesize our experimental observations, and they serve as a predictive tool to better understand the effects of perturbations.
Our work has focused on understanding the tumor suppressor protein p53. This transcription factor is upregulated in response to numerous cellular stresses, including various forms of DNA damage. When activated, it can regulate the transcription of over a hundred genes, affecting a cell's ability to repair damage, divide, or undergo programmed cell death if damage is too great. p53 is the protein most frequently mutated in cancers, and mutations in the circuit regulating p53 are believed to occur in almost all cancers.
Single-cell level analysis of the p53 regulatory circuit revealed that p53 exhibits complex dynamical behavior. In response to one form of activating stress, DNA double strand breaks, p53 can undergo a series of repeated pulses. The amplitude (p53 concentration) and the duration of individual pulses within a cell and between cells is independent of the dose of the DNA damaging agent; however, the number of pulses increases with higher doses of damage. Additionally, individual pulses of p53 are excitable -- a full p53 pulse can be triggered by either a sustained or a transient damage signal. In response to a different stress, DNA damage generated by ultraviolet (UV) radiation, p53 undergoes a distinct dynamical response. This response is graded, in that p53 shows a single pulse with amplitude and duration that directly depend on the amount of UV to which the cell is exposed. In contrast with the response to double strand breaks, this graded response to UV is not excitable. Comparison of the circuits responding to these types of damage allowed us to identify and validate, both experimentally and computationally, the molecular mechanisms responsible for the specific features of p53 dynamics we observed.
Several areas of future investigation include:
- identifying and characterizing p53's dynamical response to other forms of stress
- determining the functional consequences of p53 dynamics on p53's regulation of target genes
- extending these studies to in vivo contexts, such as normal and tumor environments in living tissue
- developing methods to manipulate p53 dynamics as a novel therapeutic strategy
- analyzing the interactions of the p53 circuit within a larger network context
- exploring other stress response circuits that show complex dynamical behaviors
Harton MD, Batchelor E. Determining the Limitations and Benefits of Noise in Gene Regulation and Signal Transduction through Single Cell, Microscopy-Based Analysis. J Mol Biol. 2017;429(8):1143-1154.
Porter JR, Telford WG, Batchelor E. Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards. J Vis Exp. 2017;(120).
Zhou W, Chung YJ, Parrilla Castellar ER, Zheng Y, Chung HJ, Bandle R, Liu J, Tessarollo L, Batchelor E, Aplan PD, Levens D. Far Upstream Element Binding Protein Plays a Crucial Role in Embryonic Development, Hematopoiesis, and Stabilizing Myc Expression Levels. Am J Pathol. 2016;186(3):701-15.
Porter JR, Fisher BE, Batchelor E. p53 Pulses Diversify Target Gene Expression Dynamics in an mRNA Half-Life-Dependent Manner and Delineate Co-regulated Target Gene Subnetworks. Cell Syst. 2016;2(4):272-82.
Purvis JE, Karhohs KW, Mock C, Batchelor E, Loewer A, Lahav G. p53 dynamics control cell fate. Science. 2012;336(6087):1440-4.
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This page was last updated on September 12th, 2019