Speaker
Manuel Razo Mejia
Description
Given the stochastic nature of gene expression, genetically identical
cells exposed to the same environmental inputs will produce different
outputs. This heterogeneity has consequences for how cells are able to
survive in changing environments. Recent work
has explored the use of information theory as a framework to
understand the accuracy with which cells can ascertain the state of
their surroundings. Yet the predictive power of these approaches is
limited and has not been rigorously tested using precision
measurements. To that end, we generate a minimal model for a simple
genetic circuit in which all parameter values for the model come from
independently published data sets. We then predict the information
processing capacity of the genetic circuit for a suite of biophysical
parameters such as protein copy number and protein-DNA affinity. We
compare these parameter- free predictions with an experimental
determination of the information processing capacity of E. coli cells,
and find that our minimal model accurately captures the experimental
data. These theoretical results will allow us to tackle the question of the
abstract quantity of information bits can serve as a quantitative trait on
which selection can act.
Primary author
Manuel Razo Mejia
