Abstract

Stress response genes and their regulators form networks that underlie drug resistance. These networks often have an inherent tradeoff: their expression is costly in the absence of stress, but beneficial in stress. They can quickly emerge in the genomes of infectious microbes and cancer cells, protecting them from treatment. Yet, the evolution of stress resistance networks is not well understood. Here, we use a two-component synthetic gene circuit integrated into the budding yeast genome to model experimentally the adaptation of a stress response module and its host genome in three different scenarios. In agreement with computational predictions, we find that: (i) intra-module mutations target and eliminate the module if it confers only cost without any benefit to the cell; (ii) intra- and extra-module mutations jointly activate the module if it is potentially beneficial and confers no cost; and (iii) a few specific mutations repeatedly fine-tune the module's noisy response if it has excessive costs and/or insufficient benefits. Overall, these findings reveal how the timing and mechanisms of stress response network evolution depend on the environment.

Details

Title
Stress-response balance drives the evolution of a network module and its host genome
Author
González, Caleb 1 ; Ray, Joe Christian J 2 ; Manhart, Michael 3 ; Adams, Rhys M 1 ; Nevozhay, Dmitry 4 ; Morozov, Alexandre V 5 ; Balázsi, Gábor 6 

 Department of Systems Biology - Unit 950, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 
 Department of Systems Biology - Unit 950, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Center for Computational Biology & Department of Molecular Biosciences, University of Kansas, Lawrence, KS, USA 
 Department of Physics & Astronomy, Rutgers University, Piscataway, NJ, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 
 Department of Systems Biology - Unit 950, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; School of Biomedicine, Far Eastern Federal University, Vladivostok, Russia 
 Department of Physics & Astronomy, Rutgers University, Piscataway, NJ, USA; BioMaPS Institute for Quantitative Biology, Rutgers University, Piscataway, NJ, USA 
 Department of Systems Biology - Unit 950, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Laufer Center for Physical & Quantitative Biology, Stony Brook University, Stony Brook, NY, USA; Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA 
Section
Articles
Publication year
2015
Publication date
Aug 2015
Publisher
EMBO Press
e-ISSN
17444292
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2289665379
Copyright
© 2015. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.