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Bioinformatics Advance Access published online on September 5, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn471
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

DESHARKY: Automatic design of metabolic pathways for optimal cell growth

Guillermo Rodrigo 1, Javier Carrera 1,2, Kristala Jones Prather 3 and Alfonso Jaramillo 4,5,*

1Instituto de Biologia Molecular y Celular de Plantas, CSIC - Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain
2Instituto de Aplicaciones en Tecnologias de la Informacion y las Comunicaciones Avanzadas (ITACA), Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain
3Department of Chemical Engineering, Massachusetts Institute of Technology, Massachusetts Avenue 77, Cambridge MA 02139, USA
4Laboratoire de Biochimie, Ecole Polytechnique - CNRS, Route de Saclay, 91128 Palaiseau Cedex, France
5Epigenomics Project, Genopole, 523 Terrasses de l'Agora, 91034 Evry Cedex, France

*To whom correspondence should be addressed. Prof. Alfonso Jaramillo, E-mail: alfonso.jaramillo{at}polytechnique.fr


  Abstract

Motivation: The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context.

Results: We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used E. coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size.

Availability: Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

Contact: alfonso.jaramillo{at}polytechnique.fr

Associate Editor: Dr. Trey ideker

Received on May 28, 2008; revised on August 14, 2008; accepted on September 2, 2008

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