Construction And Analysis Of Genome-scale Metabolic Network From Klebsiella Pneumoniae 342

It is necessary to construct and analyze the genome-scale metabolic network after the 20 years development of metabolic engineering. Although, following the development of system biology and its related study, it has been constructed over 87 genome-scale network now, each one is very time-consuming, labor-intensive, and troublesome to update. Since the complexity of biological data led to the KEGG could not directly be used to construct the metabolic network, it's necessary to build a new database, more suitable to construction of metabolic network.Klebsiella pneumoniae as a facultative anaerobe is widely used in various fermentation processes, especially in the bioconversion of glycerol to produce 1,3-propanediol due to its high conversion rate and the 1,3-propanediol production capacity. However, it has not been developed with an available way to steadily increase the yield of 1,3-propanediol through gene engineering heretofore, and it is particularly important to model and analyze its genome-scale metabolic network. Regretfully, there was no publication about the genome-scale metabolic network of Klebsiella pneumoniae.Therefore, we firstly establish a database from databases such as KEGG and Brenda. This new metabolic network database contains seven separate tables and 8601 chemical reaction records of 2471 organism, which actually suit for the modeling and analysis of metabolic network. And then, we constructed the genome-scale metabolic network of K. pneumoniae 342 based on the new database. This network totally contains 7735 records,1209 genes,2143 reaction pairs comes from 1998 reactions. The metabolic network is constructed by choosing the gene as edge and the compounds as node, respectively, which is advantage in reflecting gene information at the level of metabolic network. Moreover, it is found that the genome scale metabolic network of K. pneumoniae 342 has clustering coefficient of 0.038 which accords with power law connection degree distribution so it belongs to scale-free network which has a higher robustness against random node deletion and weakly purposeful attacking according to the theory of complex network. It also shows that the maximum path length of giant strongly connected component is 30, the radius is 16 and its characteristic path length is 8.155 which is consistent with the characteristics of small-world network. The small-word network could response quickly to the variation of the environmental factors and made the organism to adapt to the complex environment. It shows that the construction of metabolic network is convenient, fast and accurate according to our database. Therefore, the construction of genome-scale metabolic network of K. pneumoniae 342 filled the blank of this area and contributed to its dynamic research in future.