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Minimal Genome Design Algorithms Using Whole-Cell Models

Rees-Garbutt, Joshua; Chalkley, Oliver; Grierson, Claire; Marucci, Lucia


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    <dct:title>Minimal Genome Design Algorithms Using Whole-Cell Models</dct:title>
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    <dct:description>&lt;p&gt;Abstract&lt;/p&gt; &lt;p&gt;Synthetic biologists engineer cells and cellular functions using design-build-test cycles; when the task is to extensively engineer entire genomes, the lack of appropriate design tools and biological knowledge about each gene in a cell can lengthen the process, requiring time-consuming and expensive experimental iterations.&lt;/p&gt; &lt;p&gt;Whole-cell models represent a new avenue for genome design; the bacteria&amp;nbsp;&lt;em&gt;Mycoplasma genitalium&lt;/em&gt;&amp;nbsp;has the first (and currently only published) whole-cell model which combines 28 cellular submodels and represents the integrated functions of every gene and molecule in a cell.&lt;/p&gt; &lt;p&gt;We created two minimal genome design algorithms, GAMA and Minesweeper, that produced 1000s of in silico minimal genomes by running simulations on multiple supercomputers. Here we describe the steps to produce in silico cells with reduced genomes, combining minimisation algorithms with whole-cell model simulations.&lt;/p&gt; &lt;p&gt;We foresee that the combination of similar algorithms and whole-cell models could later be used for a broad spectrum of genome design applications across cellular species when appropriate models become available.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;</dct:description>
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