Research On The Analysis And Design Method Of The Metabolic Networks In The Bacteria

With the advent of post-genomic era and increasing use of compu-tational techniques, great development have taken place in compu-tational assistant which has numerous applications in systems biology and synthetic biology. There are two fields of the current microbiology research: one is the research on the microorganisms that can be cultured in the laboratory and the other is the research on the metagenome which are access directly from the nature enviorement and cannot be cultured in the laboratory. Synthetic Biology, a rapidly growing multidisciplinary field in the first field, has two complementary goals- further elucidating biological systems through mimicry and producing bioorthogonal systems with new functions. The techniques to archive these goals: search the expected metabolite routes which are exist in the natural world, predict and find new metabolite routes and design the metabolite routes manually based on the prior knowlege. One of the main uses of metagenomics is to quantify the species present in a metagenome as well as document their functional contribution to the community, however the BCP algorithm doesn't provide any of this information.In metagenomic analysis, an important component is the metabolic networks, for metabolism is a vital cellular process in the complex-ity of the underlying cellular networks in organisms. For the purpose of providing useful assistants to the biologists, we developed corresponding method and assistant system based on the metabolic networks according to the respective aquirements of the two fields metioned above. The works include: (1) The intergration of multiple metabolic databases. we have designed the process of the intergration, and developed a modified metabolite name matching alogrithm which can improve the accuracy of the matching. (2)The implementation of the metabolic route search and design system. we design and implement the metabolic route search function between two metabolites based on one or multiple organisms' networks. A compound transforming map is designed to represent the metabolic network, and also an weight function is developed to weight the edge in the graph. A metabolic route design function is developed to exploring a route from an appointed metabolite. (3) The design of method to predict the bacterial community of metagenome. We model the prediction of bacterial community to an set cover problem, and the design a modified greedy algorithm based on the biological features of the problem to solove this problem fast.The archivment of our works include: (1) An accurate and clear metabolic database is bulit after the intergration and standardization, which serves an good data base to the following researchs. (2) An user-friendly and versatile tool is bulit that can be employed in many different applications including predicting biosynthetic or catabolic routes, bio- pharmaceuticals and other related fields through the separate or complementary use of metabolic route search and design. (3) we developed a BCPI method for prediction and inference of the bacteria in the metagenomic sample. The results and analysis show that the BCPI can not only reconstruct a bacterial community which contains all the metabolic functions in the sample, but is also expandable to new functions in the sample. This method can help researchers to obtain an overview about the metagenomic samples and identify the unknown part of the sample.