Dynamic Modularity and Regulation in Protein Interaction Networks

• Main Authors: Chen-Ching Lin, 林振慶
• Other Authors: Yen-Jen Oyang
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/52053285013616237190

博士 === 國立臺灣大學 === 生醫電子與資訊學研究所 === 100 === Protein interaction networks can represent the backbone of molecular activity within cells and thus provide opportunities for understanding the mechanism of diseases. Through their influence on protein abundance, mRNA expression and microRNA regulation can affect the interaction dynamics within protein networks. Therefore, we developed an integrative analysis of protein interaction network by incorporating mRNA expression and microRNA regulation to reveal the dynamic modularity and microRNA-regulated networks in protein interaction networks. For the dynamic modularity analysis, we integrated mRNA expression profiles of a cohort of dilated cardiomyopathy patients with protein-protein interactions and found a large amount of interaction rewiring between normal and disease samples. It might suggest that the condition-specific dynamic information hid among otherwise common static interactions. We identified two heart-failure related functional modules that significantly emerged from the protein interaction networks. Additionally, the dynamic change of these modules between normal and disease states further suggested a potential molecular model of dilated cardiomyopathy. For microRNA regulations, we integrated the information of microRNA expression, target mRNA expression, and target protein-protein interaction and developed an approach to reveal microRNA-regulated protein interaction networks and to determine their functional roles in specific biological conditions. Applying this approach to investigate gastric tumor samples revealed several microRNA-regulated networks which were enriched in functions related to cancer progression. Further analyses showed that these microRNAs could be potential tumor suppressors of gastric cancer. Among them, miR-148a decreased tumor proliferation and metastasis by reducing the invasiveness, migratory and adhesive activities of tumor cells through its targets. In conclusion, we proposed a novel framework to discover the dynamic modularity and microRNA regulation embedded in the protein interaction networks in different biological states. It successfully revealed network modules closely related to heart failure and potential tumor suppressor microRNAs involved in gastric cancer. The revealed molecular modules and microRNA-regulated networks might be able to be used as potential drug targets and provide new directions for heart failure and gastric cancer therapy.