TITLE:

ANALYSIS OF THE ORGANIZATION AND DYNAMICS OF PROTEINS IN CELL MEMBRANES

DATE:

Friday, Oct 14th, 2011

TIME:

3:30 PM

LOCATION:

GMCS 214

SPEAKER:

Stanly Steinberg and Flor Espinoza
The Center for Spatiotemporal Modeling of Cell Signaling (STMC)
Department of Mathematics
Department of Pathology
University of New Mexico

ABSTRACT:

Cells communicate with the outside world through membrane
receptors that recognize one of many possible stimuli
(hormones, antibodies, peptides) in the extracellular
environment and translate this information to intracellular
responses. Changes in the organization and composition
of the plasma membrane are critical to this signal
transduction. Problems in signaling transduction are
important in understanding many diseases including cancer
and asthma. Consequently, there is considerable interest
in better understanding this signaling.

The STMC laboratories collect two types of data about
signaling: static data about the clustering of the
receptors in fixed cell membranes and dynamic data about
the motion of the receptors in living cell membranes.
In this talk, we present new methods for analyzing both
types of data. We are now in the process of using our
results to build models of the cell membrane that can
predict both types of data.

The data is obtained from both stimulated and
unstimulated cells. The unstimulated or resting cells
are not signaling. The stimulated cells are treated
with increasing amount of stimulus so that the data is
of dose-response type. The static data is obtained by
fixing the cells, removing part of the cell membrane,
labeling the intracellular part of the receptor with 5nm
in diameter gold particles and then imaging the result
with a high resolution electron microscope. The dynamic
data is obtained by labeling the extracellular part of
the membrane with an approximately 10nm quantum dots and
then tracking the motion of the quantum dots using super
resolution optical microscopy.

The analysis of the static data is done using a novel way
of quantifying the clustering that is based on hierarchical
clustering. The analysis of the dynamic data is challenging
because the quantum dots blink. If one turns off it stays
off for a long time. Conversely, it the dot turns on then
it stays on for a long time. We modified standard time
series analysis to account for this blinking and produce
information about the structure of the cell membrane on
a scale of a few tens of nanometers.

HOST:

Dr. Jose Castillo.

DOWNLOAD:

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