The Sub-cellular And Tissue Localization Of Genome-scale Human Metabolic Network

Direct in vivo investigation of human metabolism is complicated by the distinct metabolic functions of various sub-cellular organelles and tissues.sub-cellular and tissue location of gene expression and metabolic reactions is an important issue in human biological research and biomedicine development. To better understand the complexity in the human metabolism, a human metabolic network with integrated sub-cellular and tissue location information is required. In this work, we extended the previously reconstructed Edinburgh Human Metabolic Network (EHMN) by integrating the sub-cellular location, transport reactions and tissue location. Firstly, protein subcelluar location information was obtained from various databases. Then all the reactions in EHMN were assigned to subcellular locations based on protein-reaction relationships to get a preliminary compartmentalized network. We investigated the localized sub-networks in each pathway to identify gaps and isolated reactions by connectivity analysis and refined the location information based on literature. As a result, location information for hundreds of reactions was revised and hundreds of incorrect protein-reaction relationships were corrected based on the sub-cellular location. Over 1400 transport reactions were added to link the location specific metabolic network. To validate the network, we have done pathway analysis to examine the capability of the network to synthesize or degrade certain key metabolites. Using a similar approach, we added the the tissue distribution information into EHMN to reconstruct a more complete sub-cellular and tissue localized human metabolic network. As an example, we further analyzed the biological functions of mitochondria and brain using a newly developed network decomposition method. The results showed good agreements between the structurally identified modules and the pathways classified based on biofunctions. The whole network can be downloaded from www.ehmn.bioinformatics.ed.ac.uk and free for academic use.