ITLApplied  Computational Mathematics Division
ACMD Seminar Series
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Mathematical and Experimental Single-cell Analysis of Caspase Amplification in the Death Receptor Network

John M. Burke
Boehringer-Ingelheim Pharmaceuticals, Ridgefield, CT

Tuesday, December 23, 2008 11:00-12:00,
Building 101, Lecture Room C
Tuesday, December 23, 2008 09:00-10:00,
Room 4511

Abstract: Apoptotic cell death is an essential physiological process misregulated in many diseases. Understanding aspects of quantitative apoptotic regulation is a central challenge. For example, all-or-none activation of executioner caspases at the single cell level potentially has major consequences in evolution, disease, and drug resistance. While numerous theoretical mathematical models propose to explain these consequences, few are validated by direct experimental evidence. To address this challenge, a system of mass-action ordinary differential equations describing apoptotic regulation is derived and compared with extensive experimentation at the single cell level. First, model analysis identifies, and experiments verify, signal transduction control mechanisms in which the graded upstream signal induced by the initial death stimulus is converted into a rapid all-or-none downstream response. Second, the model predicts conditions under which all-or-none caspase activation fails, yielding live single cells with stable, nonzero cleaved PARP levels (substrates of cleaved executioner caspases; measure of cell death), or "undead" cells; that is, single cells that exhibit sub-lethal partial cleaved PARP levels under wild type lethal ligand doses, abrogating the all-or-none death switch. The existence of "undead" cells is experimentally validated. These undead cells proliferate, suggesting a mechanism of creating and/or perpetuating DNA-damaged cells, possibly leading to Cancer. Applying the knowledge gained from the synergy of math modeling and biology identifies key mechanisms of cellular control that, when targeted therapeutically, may alter the apoptotic fate to a more desirous outcome. Thus, computational and experimental studies have combined to generate a comprehensive model describing the caspase regulatory network and cell-to-cell variability, which accurately predicts normal and pathological behavior, which may have long lasting and critical effects curing diseases such as Cancer and controlling T cell regulation.

Speaker Bio: John Burke received his Ph.D. in Applied Mathematics at Arizona State University where he worked with Frank C. Hoppensteadt on dynamical systems theory, including bifurcation theory, singular and random perturbation theories, and modeling and analysis of cellular signaling cascades and gene expression. Upon graduation, he joined Douglas A. Lauffenburger's Lab in the Biological Engineering Department at Massachusetts Institute of Technology, as a postdoc, and later as a research faculty member. Afterwards, he joined Peter K. Sorger's Lab in the Systems Biology Department, at Harvard Medical School as a research faculty member. While at MIT and HMS, he served as co-Scientific Director of the Cell Decision Processes Center, an NIH Center of Excellence. After HMS he worked at Merrimack Pharmaceuticals, a network biology - oncology/antibody company in Cambridge, MA. Presently, he is an Associate Director of Systems Biology at Boehringer-Ingelheim Pharmaceuticals, where he is starting a new Systems Biology department.

Contact: F. Hunt

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