Carlos F. Lopez

Department of Systems Biology
Harvard Medical School

Title: Considering alternate signaling mechanisms in extrinsic apoptosis
using models as programs.

Abstract: Experiments often result in observations that suggest
conflicting biochemical mechanisms in signaling networks. Mathematical
modeling of biological systems is a method used to probe such
experimental observations and provide a consensus among seemingly
discordant observations. However, probing multiple mechanistic
hypotheses in biological modeling often involves the instantiation of
complex systems of equations, which despite their usefulness, makes
model revision, extension, and sharing extremely challenging. To address
these modeling barriers, we have developed a modeling framework that
brings a process-based approach to biological modeling. In our approach,
biological models are written as programs that encode biological
functions as needed. Our modeling framework, developed in the Python
language, offers access to a large set of existing numerical and
programming methods to biological systems modeling. Given our choice of
programming language, the resulting models are easier to share,
distribute, extend, and revise, adding transparency to the
model-creation and execution process. We demonstrate our approach by
exploring three competing mechanisms that describe the interactions
among the Bcl-2 family of proteins and their contributions to
mitochondrial outer membrane permeabilization in extrinsic apoptosis. We
used our modeling framework to systematically explore these three
proposed mechanisms resulting in the instantiation of sixteen
biochemical model topologies for numerical exploration. Our preliminary
results, based on simulations calibrated to experimental data, suggest
that the so-called indirect mechanism does not accurately reproduce
experimental observations. Results from simulations suggest that the
so-called embedded model more seems to better align with existing
experimental data. Despite these observations, further topology- and
numerical-based characterization of the model topology and
parameter-space is being carried out to more accurately understand the
role of these Bcl-2 proteins in apoptosis. We aim to formulate
hypotheses, testable through experiments, about the interaction among
these proteins and their role in Bcl-2 cancer biology.