SCIENCE AT THE EDGE SEMINAR

Friday, March 2 at 11:30am

Room 1400 Biomedical and Physical Sciences Bldg.

Refreshments at 11:15


Speaker: Dr. Phillip M. Duxbury
         Department of Physics and Astronomy
         Michigan State University

Title:   Life or death decisions in mammalian cells:
         From non-linear dynamics to control and selectivity

Abstract:

Selective control in a cell population is the ability to control a member
of the population while leaving the other members relatively unaffected.
The concept of selective control is developed using cell death
or apoptosis in heterogeneous cell populations as an example.  Apoptosis
signaling in heterogeneous cells is described by an ensemble of gene
networks with identical topology but different link strengths.  Selective
control depends on the statistics of signaling in the ensemble of
networks and we analyze the effects of the superposition, non-linearity
and feedback on these statistics.  Parallel pathways lead to normal
statistics while series pathways promote skew distributions which in the
most extreme cases become log-normal.  We also show that feedback and
non-linearity can produce bimodal signaling statistics, as can
discreteness and non-linearity.  Two methods for optimizing selective
control are presented.  The first is an exhaustive search method and the
second is a linear programming based approach.  Though control of a
single gene in the signaling network yields little selectivity, control
of a few genes typically yields high levels of selectivity.  The
statistics of gene combinations of susceptible to selective control in
heterogeneous apoptosis networks is studied and is used to identify
general control strategies.  In particular, we found a link between the
life/death switching robustness of population and optimal selectivity
strategy.  Selectivity is improved by acting on low sensitivity nodes in
weak populations and on high sensitivity nodes in robust populations, the
node sensitivity being strongly determined by the network topology.