| TGFβ(transforming growth factor), is one of the multiple function cytokines and the study of its signaling mechanism become more and more hot. Recent research suggested that the functions of TGFβsignaling pathway include cell proliferation, differentiation, cell migration and apoptosis. In different organs, this cytokines seemed to take part in various physiological and pathological processes. As we know, the inflammation reaction, tissue repairing and embryonic development are all related to TGFβsignaling. In some cases, the mutant of this pathways component could result in certain human diseases, especially in liver. For example, hepatitis, liver fibrosis, hepatocirrhosis and even liver cancer were already proved to be concerned with TGβsignaling pathway. And one goal of this research is to realize how the proteins in this pathway are organized and what kind of interaction network they were building.In our research, the large scale high-throughput screening method, Y2H (Yeast two hybrid), was used to find protein interactors in normal human liver cDNA library. For three baits, total of 125 clones were isolated as candidates. These candidates were identified by sequencing, and clones which could not match coding sequence of certain genes or not in open reading frame of genes were excluded. Finally, 87 positive results were remained and involved in 34 protein interactions, which including 23 different molecules. In these interactions, 6 of them were previous reported and the rest 28 interactions were the newly find protein interactions.The reliability of our datasets was verified by reassessment of the interactions in yeast. 33 out of all 34 interactions were still exhibiting positive phenotypes. On the other hand, we also tested those interactions in mammalian HEK293 cells by co-immunoprecipitaion. For ten interactions selected randomly, the results were all coincided with previously results. These suggested that our screening system was rather reliable. For analyzing the biological relativity of interaction proteins, the bioinformatics methods were used and combined with phenotypic profiling data. The results showed that 56% interactions whose partners had similar gene knockout phenotype, 26% protein interactors showed correlated expression with each other. In GO co-annotation analysis, 26% interaction partners appeared in the same hierarchy level even in sixth depth. And in the network topological analysis, 56% interactions were considered with high confidence. Combining all parameters in bioinformatics analysis, our estimate system (PICASSO) scored all 34 interactions and 53% (18/34) of them were up to cutoff value and taken for reliable protein interactions.Finally, we presented the interactions in visible network graphs by Cytoscape software. The networks included our dataset and certain known protein interactions related to baits or preys. In this extended graph, we performed a comprehensive analysis of biological relevance of some interactions. Together with reporter gene assay results, we presumed that certain of these new protein interactions might play new and important roles in regulation TGFβsignaling transduction pathway.In summary, we studied the protein interactions of important components in TGFβpathway by Y2H system. After verification and evaluation of the interactions by co-immunoprecipitaion, bioinformatics assay and primary function study by reporter gene assay, we gained some new partners of TGFβpathway. These interactions may help us to explore a new mode in TGFβpathway regulation especially in human liver and may provide some therapeutic target for various liver diseases.
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