An integrative approach towards completing genome-scale metabolic networks

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Item Type:	Article
Title:	An integrative approach towards completing genome-scale metabolic networks
Creators Name:	Christian, N., May, P., Kempa, S., Handorf, T. and Ebenhoeh, O.
Abstract:	Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and metabolite profiles into modeling approaches to arrive at improved gene annotations and more complete genome-scale metabolic networks. The core of our strategy is an algorithm that computes minimal sets of reactions by which a draft network has to be extended in order to be consistent with experimental observations. A particular strength of our approach is that alternative possibilities are suggested and thus experimentally testable hypotheses are produced. We carefully evaluate our strategy on the well-studied metabolic network of Escherichia coli, demonstrating how the predictions can be improved by incorporating sequence data. Subsequently, we apply our method to the recently sequenced green alga Chlamydomonas reinhardtii. We suggest specific genes in the genome of Chlamydomonas which are the strongest candidates for coding the responsible enzymes.
Keywords:	Algorithms, Chlamydomonas Reinhardtii, Ergosterol, Escherichia Coli, Genomics, Markov Chains, Metabolic Networks and Pathways, Metabolome, Metabolomics, Biological Models, Phylogeny
Source:	Molecular BioSystems
ISSN:	1742-206X
Publisher:	Royal Society of Chemistry
Volume:	5
Number:	12
Page Range:	1889-1903
Date:	December 2009
Official Publication:	https://doi.org/10.1039/B915913b
PubMed:	View item in PubMed

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