Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7

• Published in: Theoretical biology and medical modelling 2011-12, Vol.8 (1), p.47-47, Article 47
• Main Authors: Wang, Xia, Yue, Junjie, Ren, Xianwen, Wang, Yuelan, Tan, Mingfeng, Li, Beiping, Liang, Long
• Format: Article
• Language: English
• Subjects: Algorithms; Bioinformatics; Cells; Cluster analysis; Computer programs; Conserved Sequence; Cooperativity; Data processing; Databases, Protein; E coli; Escherichia coli; Escherichia coli O157 - cytology; Escherichia coli O157 - metabolism; Escherichia coli O157 - pathogenicity; Escherichia coli Proteins - metabolism; Genomes; Methods; Molecular Sequence Annotation; Multiprotein Complexes - metabolism; Pathogenicity; Pathogens; Physiological aspects; Prokaryotes; Protein interaction; Protein Interaction Maps; Protein-protein interactions; Proteins; Semantics; Sequence Homology, Amino Acid; Studies
• ISSN: 1742-4682; 1742-4682
• DOI: 10.1186/1742-4682-8-47

With the development of experimental techniques and bioinformatics, the quantity of data available from protein-protein interactions (PPIs) is increasing exponentially. Functional modules can be identified from protein interaction networks. It follows that the investigation of functional modules will generate a better understanding of cellular organization, processes, and functions. However, experimental PPI data are still limited, and no modularity analysis of PPIs in pathogens has been published to date. In this study, we predict and analyze the functional modules of E. coli O157:H7 systemically by integrating several bioinformatics methods. After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous. Six pathogenicity-related modules were discovered and analyzed, including novel modules. These modules provided new information on the pathogenicity of O157:H7. The modularity of cellular function and cooperativity between modules are also discussed. Moreover, modularity analysis of O157:H7 can provide possible candidates for biological pathway extension and clues for discovering new pathways of cross-talk. This article provides the first modularity analysis of a pathogen and sheds new light on the study of pathogens and cellular processes. Our study also provides a strategy for applying modularity analysis to any sequenced organism.