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Predicting Metabolic Pathways by Sub-network Extraction

  • Karoline Faust
  • Jacques van Helden
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 804)

Abstract

Various methods result in groups of functionally related genes obtained from genomes (operons, regulons, syntheny groups, and phylogenetic profiles), transcriptomes (co-expression groups) and proteomes (modules of interacting proteins). When such groups contain two or more enzyme-coding genes, graph analysis methods can be applied to extract a metabolic pathway that interconnects them. We describe here the way to use the Pathway extraction tool available on the NeAT Web server (http://rsat.ulb.ac.be/neat/) to piece together the metabolic pathway from a group of associated, enzyme-coding genes. The tool identifies the reactions that can be catalyzed by the products of the query genes (seed reactions), and applies sub-graph extraction algorithms to extract from a metabolic network a sub-network that connects the seed reactions. This sub-network represents the predicted metabolic pathway. We describe here the pathway prediction process in a step-by-step way, give hints about the main parametric choices, and illustrate how this tool can be used to extract metabolic pathways from bacterial genomes, on the basis of two study cases: the isoleucine–valine operon in Escherichia coli and a predicted operon in Cupriavidus (Ralstonia) metallidurans.

Key words

Metabolic pathways Pathway prediction Pathway discovery Sub-network extraction NeAT 

Notes

Acknowledgments

KF was supported by Actions de Recherches Concertées de la Communauté Française de Belgique (ARC grant number 04/09-307). The BiGRe Laboratory is supported by the Belgian Program on Interuniversity Attraction Poles, initiated by the Belgian Federal Science Policy Office, project P6/25 (BioMaGNet), and by the MICROME Collaborative Project funded by the European Commission within its FP7 Programme, under the thematic area “BIO-INFORMATICS – Microbial genomics and bio-informatics” (contract number 222886–2).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Structural BiologyResearch group of Bioinformatics and (eco-)systems biologyBrusselsBelgium
  2. 2.Microbiology Unit (MICR), Department of Applied Biological Sciences (DBIT)Vrije Universiteit BrusselBruxellesBelgium
  3. 3.Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)Université Libre de BruxellesBruxellesBelgium

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