Hello:
This is to announce a general mathematics colloqium:
Speaker: Prof. Lucas M. Stolerman, Oklahoma State University /
Machine Intelligence Lab / Boston Children's Hospital / Harvard Medical
School
Title: Stability Analysis of Reaction Models for Protein
Interaction Networks
Location: LSW 103 (big room on first floor of LSW just north of MSCS)
Time: Friday, Dec. 3, 3:30PM
Dr. Stolerman will be joining the OSU faculty this spring, and I hope
you will join us to hear about his research understanding question in
cell biology with the use of sophisticated mathematics. His abstract is
below.
Best wishes,
David Wright, Dept. of Math. OSU
Abstract:
This talk will cover two of my recent papers in
cell biology, where
local stability analysis provided insights into protein
network
dynamics. In the first paper, we investigate the
pattern formation of
a reaction-diffusion model for protein clustering in the
plasma
membrane. We obtain theoretical estimates for
diffusion-driven
instabilities of the protein aggregates based on the Turing
mechanism. Our main result is a threshold phenomenon:
a sufficiently
high feedback reaction between the membrane and
cytosolic proteins
promotes the formation of a single-patch spatially
heterogeneous
steady state. In the second paper, we discuss GTPase
molecular
switches and a network between monomeric (m) and
trimeric (t) GTPases
that have been recently found in experiments. We
develop a nonlinear
ordinary differential equation model and provide explicit
formulae
for the steady states of the system. By performing a
local stability
analysis, we systematically investigate the role of the
different
connections between the GTPase switches. Interestingly, a
coupling of
the active mGTPase to the GEF of the tGTPase is
sufficient to provide
two locally stable states that can be interpretable
biologically.
When we add a feedback loop to the coupled system,
two other locally
stable states emerge. Our findings reveal that coupling
these two
different GTPase motifs can dramatically change their
steady-state
behaviors and shed light on how such coupling may
impact signaling
mechanisms in eukaryotic cells.
