Institute Biologa Molecular Y Celular Of Plantas

Valencia, Spain

Institute Biologa Molecular Y Celular Of Plantas

Valencia, Spain

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Carrera J.,Institute Biologa Molecular Y Celular Of Plantas | Carrera J.,Genopole | Fernandez del Carmen A.,Institute Biologa Molecular Y Celular Of Plantas | Fernandez-Munoz R.,Institute Hortofruticultura Subtropical y Mediterranea La Mayora IHSM UMA CSIC | And 6 more authors.
PLoS Computational Biology | Year: 2012

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. © 2012 Carrera et al.


PubMed | Institute Biologa Molecular Y Celular Of Plantas
Type: Journal Article | Journal: PLoS computational biology | Year: 2012

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.

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