Abstract

The implementation of Boolean logic circuits in cells have become a very active field within synthetic biology. Although these are mostly focussed on the genetic components alone, the context in which the circuit performs is crucial for its outcome. We characterise 20 genetic NOT logic gates in up to 7 bacterial-based contexts each, to generate 135 different functions. The contexts we focus on are combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each gate shows seven different dynamic behaviours, depending on the context. That is, gates can be fine-tuned by changing only contextual parameters, thus improving the compatibility between gates. Finally, we analyse portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expands functionality, and advocate for considering context as a fundamental design parameter.

Genetic circuits can be engineered to generate predefined outcomes, however host context is a crucial factor in performance. Here the authors characterise twenty NOT gates in seven different bacteria to understand and predict interoperability and portability across hosts.

Details

Title
Contextual dependencies expand the re-usability of genetic inverters
Author
Tas Huseyin 1   VIAFID ORCID Logo  ; Lewis, Grozinger 2 ; Stoof Ruud 2   VIAFID ORCID Logo  ; de, Lorenzo Victor 1   VIAFID ORCID Logo  ; Goñi-Moreno, Ángel 3   VIAFID ORCID Logo 

 Systems Biology Department, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain (GRID:grid.428469.5) (ISNI:0000 0004 1794 1018) 
 Newcastle University, School of Computing, Newcastle Upon Tyne, UK (GRID:grid.1006.7) (ISNI:0000 0001 0462 7212) 
 Newcastle University, School of Computing, Newcastle Upon Tyne, UK (GRID:grid.1006.7) (ISNI:0000 0001 0462 7212); Universidad Politénica de Madrid (UPM), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Madrid, Spain (GRID:grid.419190.4) (ISNI:0000 0001 2300 669X) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2477376955
Copyright
© The Author(s) 2021. 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.