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DOE
Lowdose Radiation Program Workshop IV
Abstract
_____________________________________________________________________
Title:
Use of Computational Modeling to Evaluate Hypotheses
about the Molecular
and Cellular Mechanisms of Bystander Effects
Authors: Yuchao “Maggie” Zhao
and Rory Conolly
Institutions: CIIT Centers for Health Research,
6 Davis Drive, Research Triangle Park
North Carolina 27709, USA
A detailed understanding of the biological mechanisms of radiation-induced
damage at the molecular and cellular levels is needed for
accurate assessment of the shape of the dose-response curve
for radiationinduced health effects in the intact organism.
Computational models can contribute to the improved understanding
of mechanisms through integration of data and quantitative
evaluation of hypotheses. We propose to develop a novel computational
model of bystander effects elicited by oxidative stress and
a conceptual basis for a “biological archetype.”
The main components of the bystander effect model will be
(a) a spatial grid, with each grid element containing a single
cell, (b) a basal level of reactive oxygen species (ROS) in
each cell with incremental levels due to ionizing radiation,
(c) DNA damage due to ROS, (d) enzymatic repair of the damage,
with a capability for evaluating induction of repair as an
adaptive process linked to stress-related activation of intracellular
signaling (e) diffusion between cells of ROS and components
of the signaling pathway , (f) a cell cycle submodel that
senses the amount of DNA damage and either holds the cell
at a checkpoint, directs entry into the apoptotic pathway,
or allows progression through the next stage of the cycle
and (g) division of surviving cells to replace cells lost
to
apoptosis. Cells that progress through the cycle in the presence
of radiation-induced DNA damage will have a proportionately
increased probability of mutation. Background and radiation-induced
oxidative stress in directly hit and bystander cells will
thus be associated with a suite of possible outcomes including
(1) no adverse effect, (2) DNA damage, (3) apoptosis, (4)
cellular proliferation and (5) accumulation of mutations.
The model will be parameterized against data to the greatest
degree possible and will be capable of both posing and evaluating
hypotheses about the development and consequences of bystander
effects at the molecular, cellular, and tissue levels. Our
proposal for a biological archetype will draw on our experience
in developing computational models of whole-body pharmacokinetic
mechanisms of environmental chemicals where key biological
processes and structures are described in detail, while nonessential
components are lumped together. The archetype will be capable
of integrating mechanistic information across the relevant
levels of biological organization to predict adverse health
effects in intact organisms. We expect that the archetype
will not be a single, large, complex model but rather a suite
of models with due attention paid to programming standardization
and capabilities for intermodel communication. Together, these
efforts will demonstrate a rigorous computational modeling
approach to the evaluation of hypotheses for mechanisms of
bystander effects and contribute to development of a conceptual
framework for the use of molecular level mechanistic data
in human health risk assessment.
