Journal article Open Access

Furthering genome design using models and algorithms

Rees-Garbutt, Joshua; Rightmyer, Jake; Karr, Jonathan R.; Grierson, Claire; Marucci, Lucia


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    <subfield code="u">Icahn Institute for Data Science and Genomic Technology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA</subfield>
    <subfield code="a">Karr, Jonathan R.</subfield>
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    <subfield code="u">Department of Engineering Mathematics, University of Bristol, Bristol, BS8 1UB, UK</subfield>
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    <subfield code="a">Furthering genome design using models and algorithms</subfield>
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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Highlights&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;Models can investigate many more genome designs than laboratory research.&lt;/li&gt;
	&lt;li&gt;Algorithms can search for genomes that optimise specific criteria.&lt;/li&gt;
	&lt;li&gt;Together, models and algorithms can help engineers to design genomes.&lt;/li&gt;
	&lt;li&gt;Algorithm-driven whole-cell model&amp;nbsp;&lt;em&gt;in silico&lt;/em&gt;&amp;nbsp;designs could be viable&amp;nbsp;&lt;em&gt;in&amp;nbsp;vivo&lt;/em&gt;.&lt;/li&gt;
	&lt;li&gt;The genome design ecosystem needs improved modelling and design tools.&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Abstract&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Large-scale&amp;nbsp;&lt;em&gt;in silico&lt;/em&gt;&amp;nbsp;genome designs are on the brink of being engineered&amp;nbsp;&lt;em&gt;in&amp;nbsp;vivo&lt;/em&gt;, offering a potential paradigm shift for cellular research (previous designs relied on fractured available knowledge and&amp;nbsp;&lt;em&gt;in&amp;nbsp;vivo&lt;/em&gt;&amp;nbsp;engineering iteration) by integrating computational design,&amp;nbsp;&lt;em&gt;in silico&lt;/em&gt;&amp;nbsp;models and algorithms, with laboratory construction. However, several challenges remain. If&amp;nbsp;&lt;em&gt;in&amp;nbsp;vivo&lt;/em&gt;&amp;nbsp;engineering is successful, designing genomes can be used to gain new understanding of cellular life, improve the metabolite production process and reduce the risk of unintended genetic modification and release. Here, we review the progress so far. We suggest improvements on recent models and algorithms, illustrate the next steps for integrating computational and laboratory engineering and offer our opinions on the future of the field.&lt;/p&gt;</subfield>
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