4836284
doi
10.1016/j.coisb.2020.10.006
oai:zenodo.org:4836284
user-eu
di Bernardo, Mario
1 Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol, UK 2 BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK 3 Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, Napoli, Italy
Gorochowski, Thomas E.
BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK - School of Biological Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK
Self-adaptive biosystems through tunable genetic parts and circuits
Bartoli, Vittorio
Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol, UK
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
<p>Abstract</p>
<p>Biological systems often need to operate in complex environments where conditions can rapidly change. This is possible because of their inherent ability to sense changes and adapt their behavior in response. Here, we detail recent advances in the creation of synthetic genetic parts and circuits whose behaviors can be dynamically tuned through a variety of intracellular and extracellular signals. We show how this capability lays the foundation for implementing control engineering schemes in living cells and allows for the creation of biological systems that are able to self-adapt, ensuring their functionality is maintained in the face of varying environmental and physiological conditions. We end by discussing some of the broader implications of this technology for the safe deployment of synthetic biology.</p>
<p> </p>
Zenodo
2020-10-14
info:eu-repo/semantics/article
4836283
user-eu
award_title=Control Engineering of Biological Systems for Reliable Synthetic Biology Applications; award_number=766840; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/766840; funder_id=00k4n6c32; funder_name=European Commission;
1622341246.971274
1165461
md5:ab85efa294ea0b23b9f9d2f5003a2bdb
https://zenodo.org/records/4836284/files/Bartoli et al 2020 .pdf
public
Current Opinion in System Biology
24
78-85
2020-10-14