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PLoS Comput Biol. 2012;8(6):e1002528. doi: 10.1371/journal.pcbi.1002528. Epub 2012 Jun 7.

Fine-tuning tomato agronomic properties by computational genome redesign.

Author information

1
Instituto de Biologa Molecular y Celular de Plantas, Consejo Superior de Investigaciones Cientificas-UPV, Valencia, Spain. Javier.Carrera@synth-bio.org

Abstract

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites.

PMID:
22685389
PMCID:
PMC3369923
DOI:
10.1371/journal.pcbi.1002528
[Indexed for MEDLINE]
Free PMC Article
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