Exploring the structural topology of genome-based large-scale metabolic network is essential for in- vestigating possible relations between structure and functionality.Visualization would be helpful for obtaining immediate information about structural organization.In this work,metabolic networks of 75 organisms were investigated from a topological point of view.A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks.The revealed topological pattern helps to design more efficient algorithm specifically for metabolic networks.This coarse- grained graph also visualizes the vulnerable connections in the network,and thus could have important implication for disease studies and drug target identifications.In addition,analysis on the reciprocal links and main cores in the GSC part of bow-tie also reveals that the bow-tie structure of metabolic networks has its own intrinsic and significant features which are significantly different from those of random networks. Exploring the structural topology of genome-based large-scale metabolic network is essential for-vestigating possible relations between structure and functionality. Visualization would be helpful for acquiring immediate information about structural organization. In this work, metabolic networks of 75 organisms were investigated from a topological point of view. A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks. The revealed topological pattern helps to design more efficient algorithm specifically for metabolic networks. This coarse-grained graph also visualizes the vulnerable connections in the network, and thus could have important implication for disease studies and drug target identifications. In addition, analysis on the reciprocal links and main cores in the GSC part of bow-tie also reveals that the bow-tie structure of metabolic networks has its own intrinsic and significant features which are significantly different fro m those of random networks.