Journal article Open Access

Self-adaptive biosystems through tunable genetic parts and circuits

Bartoli, Vittorio; di Bernardo, Mario; Gorochowski, Thomas E.


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  <identifier identifierType="URL">https://zenodo.org/record/4836284</identifier>
  <creators>
    <creator>
      <creatorName>Bartoli, Vittorio</creatorName>
      <givenName>Vittorio</givenName>
      <familyName>Bartoli</familyName>
      <affiliation>Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol, UK</affiliation>
    </creator>
    <creator>
      <creatorName>di Bernardo, Mario</creatorName>
      <givenName>Mario</givenName>
      <familyName>di Bernardo</familyName>
      <affiliation>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</affiliation>
    </creator>
    <creator>
      <creatorName>Gorochowski, Thomas E.</creatorName>
      <givenName>Thomas E.</givenName>
      <familyName>Gorochowski</familyName>
      <affiliation>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</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Self-adaptive biosystems through tunable genetic parts and circuits</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <dates>
    <date dateType="Issued">2020-10-14</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4836284</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.coisb.2020.10.006</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Abstract&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/766840/">766840</awardNumber>
      <awardTitle>Control Engineering of Biological Systems for Reliable Synthetic Biology Applications</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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