Reference : Towards improved genome-scale metabolic network reconstructions: unification, transcr...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/22766
Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond.
English
Pfau, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit]
Pacheco, Maria Irene mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit]
2015
Briefings in bioinformatics
Yes (verified by ORBilu)
International
1467-5463
1477-4054
[en] gene-protein-reaction association ; metabolic network reconstruction ; unification
[en] Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from prokaryotes to higher organisms and methods for the analysis of a reconstruction. One example is the use of flux balance analysis to improve the yields of a target chemical, which has been applied successfully. However, comparison of results between existing reconstructions and models presents a challenge because of the heterogeneity of the available reconstructions, for example, of standards for presenting gene-protein-reaction associations, nomenclature of metabolites and reactions or selection of protonation states. The lack of comparability for gene identifiers or model-specific reactions without annotated evidence often leads to the creation of a new model from scratch, as data cannot be properly matched otherwise. In this contribution, we propose to improve the predictive power of metabolic models by switching from gene-protein-reaction associations to transcript-isoform-reaction associations, thus taking advantage of the improvement of precision in gene expression measurements. To achieve this precision, we discuss available databases that can be used to retrieve this type of information and point at issues that can arise from their neglect. Further, we stress issues that arise from non-standardized building pipelines, like inconsistencies in protonation states. In addition, problems arising from the use of non-specific cofactors, e.g. artificial futile cycles, are discussed, and finally efforts of the metabolic modelling community to unify model reconstructions are highlighted.
Researchers
http://hdl.handle.net/10993/22766
(c) The Author 2015. Published by Oxford University Press.

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