Journal article Open Access

Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology

Marucci, Lucia; Barberis, Matteo; Karr, Jonathan; Ray, Oliver; Race, Paul R.; Andrade, Miguel de Souza; Grierson, Claire; Hoffmann, Stefan Andreas; Landon, Sophie; Rech, Elibio; Rees-Garbutt, Joshua; Seabrook, Richard; Shaw, William; Woods, Christopher


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    <subfield code="u">4Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom 5Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, United Kingdom 6Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life</subfield>
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    <subfield code="a">Karr, Jonathan</subfield>
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    <subfield code="u">Department of Computer Science, University of Bristol, Bristol, United Kingdom</subfield>
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    <subfield code="u">Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom</subfield>
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    <subfield code="a">Andrade, Miguel de Souza</subfield>
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    <subfield code="u">Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom - School of Biological Sciences, University of Bristol, Bristol, United Kingdom</subfield>
    <subfield code="a">Grierson, Claire</subfield>
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    <subfield code="u">Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom</subfield>
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    <subfield code="u">Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom - Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom</subfield>
    <subfield code="a">Landon, Sophie</subfield>
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    <subfield code="u">Brazilian Agricultural Research Corporation/National Institute of Science and Technology – Synthetic Biology, Brasília, Brazil</subfield>
    <subfield code="a">Rech, Elibio</subfield>
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    <subfield code="a">Rees-Garbutt, Joshua</subfield>
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    <subfield code="u">Elizabeth Blackwell Institute for Health Research (EBI), University of Bristol, Bristol, United Kingdom</subfield>
    <subfield code="a">Seabrook, Richard</subfield>
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    <subfield code="u">Department of Bioengineering, Imperial College London, London, United Kingdom</subfield>
    <subfield code="a">Shaw, William</subfield>
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    <subfield code="u">Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom - School of Chemistry, University of Bristol, Bristol, United Kingdom</subfield>
    <subfield code="a">Woods, Christopher</subfield>
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    <subfield code="c">2020-08-07</subfield>
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    <subfield code="p">Frontiers in Bioengineering and Biotechnology</subfield>
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    <subfield code="u">1Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom 2School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom 3Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom</subfield>
    <subfield code="a">Marucci, Lucia</subfield>
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    <subfield code="a">Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology</subfield>
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    <subfield code="c">766840</subfield>
    <subfield code="a">Control Engineering of Biological Systems for Reliable Synthetic Biology Applications</subfield>
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    <subfield code="a">&lt;p&gt;Abstract&lt;/p&gt;

&lt;p&gt;Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells&amp;nbsp;&lt;em&gt;in silico&lt;/em&gt;offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.&lt;/p&gt;</subfield>
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    <subfield code="a">10.3389/fbioe.2020.00942</subfield>
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