Minimal Genome Design Algorithms Using Whole-Cell Models

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)183-198
Number of pages16
JournalMethods in Molecular Biology
Volume2189
DOIs
Publication statusPublished - 13 Nov 2020

Bibliographical note

Funding Information:
LM is supported by the Medical Research Council grant MR/N021444/1, by the Engineering and Physical Sciences Research Council grants EP/R041695/1 and EP/S01876X/1, and by the European Union?s Horizon 2020 under Grant Agreement No. 766840. OC, LM and CG are supported by a BrisSyn-Bio, a BBSRC/EPSRC Synthetic Biology Research Centre (BB/L01386X/1), flexi-fund grant. OC is supported by the Bristol Centre for Complexity Sciences (BCCS) Centre for Doctoral Training (CDT) EP/I013717/1. JR-G is supported by an EPSRC Future Opportunity scholarship.

Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • Algorithms
  • Computer Simulation
  • Genetic Engineering
  • Genome, Bacterial
  • Models, Genetic
  • Mycoplasma genitalium/genetics
  • Synthetic Biology

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