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PLoS Comput Biol. 2014 Feb 6;10(2):e1003465. doi: 10.1371/journal.pcbi.1003465. eCollection 2014 Feb.

Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species.

Author information

1
Department of Computer Science, University of Helsinki, Helsinki, Finland ; Department of Medical Genetics, Genome-Scale Biology Research Program, University of Helsinki, Helsinki, Finland.
2
VTT Technical Research Centre of Finland, Espoo, Finland.
3
Department of Computer Science, University of Helsinki, Helsinki, Finland ; Department of Information and Computer Science, Aalto University, Espoo, Finland.
4
Department of Information and Computer Science, Aalto University, Espoo, Finland.
5
Institute of Biotechnology & Department of Biosciences, University of Helsinki, Helsinki, Finland.

Abstract

We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

PMID:
24516375
PMCID:
PMC3916221
DOI:
10.1371/journal.pcbi.1003465
[Indexed for MEDLINE]
Free PMC Article

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