First-principles prediction of the information processing
1
capacity of a simple genetic circuit
2
Manuel Razo-Mejia
1
and Rob Phillips
1, 2, 3, *
3
1
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
4
2
Department of Physics, California Institute of Technology, Pasadena, CA 91125, USA
5
3
Department of Applied Physics, California Institute of Technology, Pasadena, CA 91125, USA
6
*
Correspondence: phillips@pboc.caltech.edu
7
8
Abstract
9
Given the stochastic nature of gene expression, genetically identical cells exposed to the same
10
environmental inputs will produce di
↵
erent outputs. This heterogeneity has consequences for how
11
cells are able to survive in changing environments. Recent work has explored the use of information
12
theory as a framework to understand the accuracy with which cells can ascertain the state of their
13
surroundings. Yet the predictive power of these approaches is limited and has not been rigorously
14
tested using precision measurements. To that end, we generate a minimal model for a simple genetic
15
circuit in which all parameter values for the model come from independently published data sets.
16
We then predict the information processing capacity of the genetic circuit for a suite of biophysical
17
parameters such as protein copy number and protein-DNA a