MetaRec:a System For Reconstruct Microbe’s Metabolism Network

Metabolic processes which constituted by genes, enzymes, small molecules and reac-tions are the foundation of all living organisms. The metabolic network reconstruction can intergrately analyze and comprehend the genome information. It is a process which identi-fies, classifies and interlinks metabolism network participants plays an important role in analyzing and understanding metabolic activity. In the post-genomic era, a large amount of long-accumulated genomic data can make systematically reconstruct metabolic network possible. The current reconstruction of metabolic network mainly utilizes existing biologi-cal knowledge. But now it is still lack of an underlying-data standard and its perspective is only based on pathway.For resolving these problems, we design and implement a system named MetaRec for metabolic network semi-automated reconstruction based on underlying-data integration strategy. This system could efficiently reconstruct prokaryote’s metabolic network from its genome information. The characteristics of MetaRec are as follow:MetaRec integrated and curated several metabolic related databases and indexed as a local non-redundant data resource. This curated dataset could offer an integrated source for metabolic reconstruction research.NCBI pylogenetic tree was utilized for guiding the EC assignment in the process of gene function annotation in MetaRec. Experimental and analytical results show this strate-gy is more efficient than KEGG’s annotation method.Finally, we authenticate the efficiency and accuracy of our system by reconstructing the metabolic network of Actinobacillus pleuropneumoniae JL03. Compared with KEGG, the result could significant improve annotation accuracy and analysis efficiency.MetaRec has advantages for both automated and manual reconstruction method. It has good application value and theoretical significance for reconstructing unknown organism’s metabolic network based on its genome information and further understanding metabolism function of organisms.