Integration of metabolome data with metabolic networks reveals reporter reactions.

@article{citeulike:1562121, abstract = {Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through combination of metabolome and transcriptome data.}, address = {Department of Chemical Engineering, Bo\u{g}aziçi University, Bebek, Istanbul, Turkey.}, author = {Cakir, T. and Patil, K. R. and Onsan, Z. and Ulgen, K. O. and Kirdar, B. and Nielsen, J. }, citeulike-article-id = {1562121}, doi = {http://dx.doi.org/10.1038/msb4100085}, issn = {1744-4292}, journal = {Mol Syst Biol}, keywords = {metabolism, systems\_biology}, posted-at = {2007-08-15 09:08:12}, priority = {4}, title = {Integration of metabolome data with metabolic networks reveals reporter reactions.}, url = {http://dx.doi.org/10.1038/msb4100085}, volume = {2}, year = {2006} }

TY - JOUR ID - citeulike:1562121 L3 - citeulike-article-id:1562121 TI - Integration of metabolome data with metabolic networks reveals reporter reactions. JF - Mol Syst Biol VL - 2 AD - Department of Chemical Engineering, Boğaziçi University, Bebek, Istanbul, Turkey. SN - 1744-4292 N2 - Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through combination of metabolome and transcriptome data. KW - metabolism KW - systems_biology AU - Cakir, T AU - Patil, KR AU - Onsan, Z AU - Ulgen, KO AU - Kirdar, B AU - Nielsen, J PY - 2006/// UR - http://dx.doi.org/10.1038/msb4100085 ER -