A Protein Intetaction Network Focused On Regulators Of Tumour Suppressor P53

The tumor suppressor p53 regulates cell cycle arrest, apoptosis and DNA repair processes by controlling various target genes that contain p53 sequence-specific DNA binding sites. In response to a broad range of cellular stresses, such as DNA damage, aberrant oncogene activation or lack of oxygen (hypoxia), p53 accumulates in the cell and thereby becomes activated. Generally, p53 protein accumulation is not considered to be due to an enhanced transcriptional response of the cell but the consequence of p53 protein stabilization as a consequence of a range of post-translational modifications, such as phosphorylation, acetylation, ubiquitination and methylation.Large-scale elucidation of protein-protein interaction patterns provides an important basic dataset in the functional analysis of the proteome. In this disertation, we focused on p53 regulator's protein-protein interaction network in human liver by modular-scale yeast two-hybrid library screening.Thirty four baits were successfully constructed, including the proteins which can regulate p53 by phosphorylation, acetylation, ubiquitination and methylation, etc. These baits were screened against human liver cDNA library. 458 preys (AD-Y) identities were determined with interaction sequence tags (ISTs) by sequencing. After removal of non-coding DNA sequences and the out of frame sequences, 106 different protein interaction pairs involved 108 proteins were obtained, among which 11 interactions were known. To estimate our technical false positive rate, all interactions were verified by retransformation in yeast cells. The total recovery rate for the interactions was 67%. To evaluate the accuracy of the Y2H datasets, a randomly selected Y2H interaction pairs were tested by a co-immunoprecipitation (co-IP) assay. The co-IP success rates were 13 out of 18(72%).Several independent bioinformatics analysis were used to evaluate the potential biological relevance of the identified interactions. By searching the PubMed and HPRD databases for co-occurrence of the corresponding gene symbols, we found 17 interactions (16%) whose partners show linkage of the corresponding gene symbols. According to the mouse genome informatics data, we found 16 interactions whose partners show similar gene knockout phenotype. Our interactions were also investigated by GO annotation. We found that 64 interactions share same cellular component, 28 interactions share same molecular function, and 38 interactions participate in the same biological process. By the interacting domain analysis based on InterPro database, we found 25 interactions contain interacting domains. These results indicate that our interactions are of high confidence. Using experimental and bioinformatics analysis information, we established a scoring system for confidence evaluation. Each interaction was scored with this system and then grouped into three confidence sets according to their score, resulting in 40 interactions (38%) with high confidence, 42 interactions (40% of our interactions) with medium confidence and 24 interactions (22% of our interactions) with low confidence.In addition to estimate the fidelity of Y2H data sets, we presented the interactions in visible network graphs with Osprey network visualization system. The network shows that our dataset is complement for the existent network. By integrating the experimental and vavious confidence evaluation information, as well as by literature mining, we performed a comprehensive analysis of the biological relevance of some interactions. These results may provide some important clues for the functional analysis of the interactions.We confirmed the interaction between an ubiquitin ligase MDM2 and a ribosomal protein L26 and observed that RPL26 modulates the MDM2–p53 interaction by forming a ternary complex among RPL26, MDM2 and p53, which leads to the stabilization and activation of p53 via inhibiting the ubiquitin ligase activity of MDM2. These observations provide an additional regulatory mechanism associated with RPL26's function in regulating p53.In conclusion, this dissertation presents a network for p53 regulation pathway by Y2H screening, which might be useful for understanding the p53 regulation mechanism and function in the physiological and pathological process of human liver.