Data from whole-cell modelling (12-2019)

In the future, entire genomes tailored to specific functions and environments could be designed using computational tools. However, computational tools for genome design are currently scarce. Here we present algorithms that enable the use of design-simulate-test cycles for genome design, using genome minimisation as a proof-of-concept. Minimal genomes are ideal for this purpose as they have a simple functional assay whether the cell replicates or not. We used the first (and currently only published) whole-cell model for the bacterium Mycoplasma genitalium. Our computational design-simulate-test cycles discovered novel in-silico minimal genomes which, if biologically correct, predict in-vivo genomes smaller than JCVI-Syn3.0; a bacterium with, currently, the smallest genome that can be grown in pure culture. In the process, we identified 10 low essential genes and produced evidence for at least two Mycoplasma genitalium in-silico minimal genomes. This work brings combined computational and laboratory genome engineering a step closer.

Alternative title Minimal Genome Design Algorithms using whole-cell models Rees-Garbutt and Chalkley et al 2019
Creator(s) Lucia Marucci, Claire Grierson, Oliver Chalkley, Joshua Rees, Sophia Landon
Publication date 13 Dec 2019
Language eng
Publisher University of Bristol
Licence Non-Commercial Government Licence for public sector information
DOI 10.5523/bris.1jj0fszzrx9qf2ldcz654qp454
Complete download (zip)
Citation Lucia Marucci, Claire Grierson, Oliver Chalkley, Joshua Rees, Sophia Landon (2019): Data from whole-cell modelling (12-2019).
Total size 99.7 GiB


Data Resources