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,
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
Building 101, Lecture Room C
Tuesday, December 23, 2008 09:00-10:00,
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
Note: Visitors from outside NIST must contact
Robin Bickel; (301) 975-3668;
at least 24 hours in advance.