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First-principles prediction of the information processing capacity of a simple genetic circuit

Razo-Mejia, Manuel and Phillips, Rob (2019) First-principles prediction of the information processing capacity of a simple genetic circuit. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20190402-080512452

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Abstract

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.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/594325DOIDiscussion Paper
ORCID:
AuthorORCID
Razo-Mejia, Manuel0000-0002-9510-0527
Phillips, Rob0000-0003-3082-2809
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license. bioRxiv preprint first posted online Mar. 31, 2019. The authors would like to acknowledge Griffin Chure, Muir Morrison, and Nathan Belliveau for fruitful discussions. We would like to also thank William Bialek, Emanuel Flores, Hernan Garcia, Alejandro Granados, Jane Kondev, Sarah Marzen, Porfirio Quintero, Alvaro Sanchez, Rachel Taub man, Gašper Tkačik, Catherine Triandafillou, and Ned Wingreen for useful advice and discussion. We thank Rob Brewster for providing the raw mRNA FISH data for inferences, Heun-Jin Lee for support with the quantitative microscopy, and David Drabold for advice on the maximum entropy inferences. This work was supported by La Fondation Pierre-Gilles de Gennes, the Rosen Center at Caltech, and the NIH 1R35 GM118043 (MIRA).
Group:Rosen Bioengineering Center
Funders:
Funding AgencyGrant Number
La Fondation Pierre-Gilles de GennesUNSPECIFIED
Donna and Benjamin M. Rosen Bioengineering CenterUNSPECIFIED
NIH1R35 GM118043-01
Record Number:CaltechAUTHORS:20190402-080512452
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190402-080512452
Official Citation:First-principles prediction of the information processing capacity of a simple genetic circuit. Manuel Razo-Mejia, Rob Phillips. bioRxiv 594325; doi: https://doi.org/10.1101/594325
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:94350
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:02 Apr 2019 15:33
Last Modified:15 May 2019 16:26

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