Published November 13, 2020 | Version v1
Preprint Open

Minimal Genome Design Algorithms Using Whole-Cell Models

  • 1. 1 BrisSynBio, University of Bristol, Bristol BS8 1TQ, UK; 2 School of Biological Sciences, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK
  • 2. 3 Department of Engineering Mathematics, University of Bristol, Bristol BS8 1UB, UK; 4 Bristol Centre for Complexity Science, Department of Engineering Mathematics, University of Bristol, Bristol BS8 1UB, UK
  • 3. 1 BrisSynBio, University of Bristol, Bristol BS8 1TQ, UK; 3 Department of Engineering Mathematics, University of Bristol, Bristol BS8 1UB, UK; 5 School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1UB, UK.

Description

Abstract

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.

Whole-cell models represent a new avenue for genome design; the bacteria Mycoplasma genitalium 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.

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.

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.

 

 

 

Files

Rees-Garbutt et al 2021 Computational Methods in Synthetic Biology.pdf

Files (721.8 kB)

Additional details

Funding

European Commission
COSY-BIO - Control Engineering of Biological Systems for Reliable Synthetic Biology Applications 766840