Preprint Open Access

Balancing Cell Populations Endowed with a Synthetic Toggle Switch via Adaptive Pulsatile Feedback Control

Guarino, Agostino; Fiore, Davide; Salzano, Davide

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<identifier identifierType="URL">https://zenodo.org/record/4809877</identifier>
<creators>
<creator>
<creatorName>Guarino, Agostino</creatorName>
<givenName>Agostino</givenName>
<familyName>Guarino</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3951-8929</nameIdentifier>
<affiliation>Department of Electrical Engineering and Information Technology, University of Naples Federico II</affiliation>
</creator>
<creator>
<creatorName>Fiore, Davide</creatorName>
<givenName>Davide</givenName>
<familyName>Fiore</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4011-5836</nameIdentifier>
<affiliation>Department of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II</affiliation>
</creator>
<creator>
<creatorName>Salzano, Davide</creatorName>
<givenName>Davide</givenName>
<familyName>Salzano</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2171-4745</nameIdentifier>
<affiliation>Department of Electrical Engineering and Information Technology, University of Naples Federico II</affiliation>
</creator>
</creators>
<titles>
<title>Balancing Cell Populations Endowed with a Synthetic Toggle Switch via Adaptive Pulsatile Feedback Control</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2020</publicationYear>
<dates>
<date dateType="Issued">2020-03-12</date>
</dates>
<resourceType resourceTypeGeneral="Text">Preprint</resourceType>
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<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4809877</alternateIdentifier>
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<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1021/acssynbio.9b00464</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/cosy-bio</relatedIdentifier>
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<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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<descriptions>
<description descriptionType="Abstract">&lt;p&gt;Abstract&lt;/p&gt;

&lt;p&gt;The problem of controlling cells endowed with a genetic toggle switch has been recently highlighted as a benchmark problem in synthetic biology. It has been shown that a carefully selected periodic forcing can balance a population of such cells in an undifferentiated state. The effectiveness of these control strategies, however, can be hindered by the presence of stochastic perturbations and uncertainties typically observed in biological systems and is therefore not robust. Here, we propose the use of feedback control strategies to enhance robustness and performance of the balancing action by selecting in real-time both the amplitude and the duty-cycle of the pulsatile inputs affecting the toggle switch behavior. We show,&amp;nbsp;&lt;em&gt;via&lt;/em&gt;&lt;em&gt;in silico&lt;/em&gt;experiments and realistic agent-based simulations, the effectiveness of the proposed strategies even in the presence of uncertainties, stochastic effects, cell growth, and inducer diffusion. In so doing, we confirm previous observations made in the literature about coherence of the population when pulsatile forcing inputs are used, but, contrary to what was proposed in the past, we leverage feedback control techniques to endow the balancing strategy with unprecedented robustness and stability properties. We compare&amp;nbsp;&lt;em&gt;via&lt;/em&gt;&lt;em&gt;in silico&lt;/em&gt;&amp;nbsp;experiments different external control solutions and show their advantages and limitations from an&amp;nbsp;&lt;em&gt;in vivo&lt;/em&gt;&amp;nbsp;implementation viewpoint.&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>
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