Abstract

Many essential bacterial responses present complex transcriptional regulation of gene expression. To what extent can the study of these responses substantiate the logic of their regulation? Here, we show how the input function of the genes constituting the response, i.e., the information of how their transcription rates change as function of the signals acting on the regulators, can serve as a quantitative tool to deconstruct the corresponding regulatory logic. To demonstrate this approach, we consider the multiple antibiotic resistance (mar) response in Escherichia coli. By characterizing the input function of its representative genes in wild-type and mutant bacteria, we recognize a dual autoregulation motif as main determinant of the response, which is further adjusted by the interplay with other regulators. We show that basic attributes, like its reaction to a wide range of stress or its moderate expression change, are associated with a strong negative autoregulation, while others, like the buffering of metabolic signals or the lack of memory to previous stress, are related to a weak positive autoregulation. With a mathematical model of the input functions, we identify some constraints fixing the molecular attributes of the regulators, and also notice the relevance of the bicystronic architecture harboring the dual autoregulation that is unique in E. coli. The input function emerges then as a tool to disentangle the rationale behind most of the attributes defining the mar phenotype. Overall, the present study supports the value of characterizing input functions to deconstruct the complexity of regulatory architectures in prokaryotic and eukaryotic systems.

Details

Title
Deconstructing a multiple antibiotic resistance regulation through the quantification of its input function
Author
Rodrigo, Guillermo 1 ; Bajić, Djordje 2 ; Elola, Ignacio 3 ; Poyatos, Juan F 3 

 Instituto de Biología Molecular y Celular de Plantas, CSIC–UPV, Valencia, Spain 
 Logic of Genomic Systems Laboratory, CNB–CSIC, Madrid, Spain; Department of Ecology and Evolutionary Biology, Yale University, New Haven, USA 
 Logic of Genomic Systems Laboratory, CNB–CSIC, Madrid, Spain 
Pages
1-9
Publication year
2017
Publication date
Oct 2017
Publisher
Nature Publishing Group
e-ISSN
20567189
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1947856846
Copyright
© 2017. 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.