發(fā)布時間：2018-08-15 16:18

【摘要】：近年來，高通量技術(shù)在生物醫(yī)學研究中的應(yīng)用導致了大量生物數(shù)據(jù)的積累。這些數(shù)據(jù)涉及基因與蛋白質(zhì)序列，DNA微陣列和生物醫(yī)學圖像等。為了利用這些數(shù)據(jù)發(fā)現(xiàn)可應(yīng)用于生物醫(yī)學研究的信息，數(shù)據(jù)挖掘技術(shù)得以開發(fā)和發(fā)展。在生物醫(yī)學研究中，數(shù)據(jù)挖掘技術(shù)發(fā)揮了越來越重要的作用，并已成為生物醫(yī)學發(fā)現(xiàn)過程的一部分。在我們的研究中，我們應(yīng)用數(shù)據(jù)挖掘技術(shù)，首次從HepG2細胞的表達譜芯片中提煉出有效信息，創(chuàng)新性的預測了NDRG2的轉(zhuǎn)錄調(diào)控因子及NDRG2與Dusp6的相互作用分子。 由于NDRG2在腫瘤細胞中的表達是降低的，為了全面理解NDRG2對腫瘤細胞的生物學效應(yīng)，我們用表達譜芯片檢測了HepG2細胞的基因表達，并對芯片數(shù)據(jù)進行了富集度分析。GO生物學過程分析表明參與G蛋白信號轉(zhuǎn)導的基因表達增加了。我們選擇其中5個基因進行qRT-PCR驗證。而參與細胞M期的基因則降低了，這與細胞周期的分析結(jié)果一致。信號通路分析表明與血細胞分化和細胞粘附有關(guān)的分子表達明顯增加，與蛋白的GPI修飾，蛋白降解和細胞分泌相關(guān)的基因表達降低。進一步通過模體分析和實驗驗證，我們發(fā)現(xiàn)NDRG2可以增加p38的磷酸化水平。通過富集度分析，我們成功從芯片數(shù)據(jù)中提取了有效信息，并為理解NDRG2在腫瘤細胞中的作用機制提供分子基礎(chǔ)。 為了理解NDRG2在不同條件下的表達模式，我們創(chuàng)新性的使用ARACNE算法和模體掃描預測了調(diào)節(jié)NDRG2表達的轉(zhuǎn)錄因子。通過模體掃描，我們發(fā)現(xiàn)在NDRG2啟動子區(qū)域有129個轉(zhuǎn)錄因子的結(jié)合位點。為了提高預測的精確性，我們用ARACNE算法來估算NDRG2與這些轉(zhuǎn)錄因子的相關(guān)性。最終，我們得到了53個可能調(diào)節(jié)NDRG2基因表達的候選轉(zhuǎn)錄因子。在這些轉(zhuǎn)錄因子中，由于KLF4可以誘導結(jié)腸癌細胞分化，我們選擇KLF4進行實驗驗證。對這些轉(zhuǎn)錄因子的功能分析表明，它們主要與細胞分化，器官發(fā)育和細胞內(nèi)物質(zhì)的運輸和定位有關(guān)。這與之前的研究結(jié)果是一致。 最后，為了發(fā)現(xiàn)NDRG2的相互作用分子，我們搜索了NDRG2在擬南芥中的同源物，并鑒定出NDL1,NDL2和NDL3為NDRG2的同源蛋白。這些NDL蛋白曾被報道可以與AGB1和RGS1相互作用，這提示NDRG2可以與這兩個分子的人的同源物相互作用。AGB1為G蛋白三聚物的β亞單位。在人中，有5個AGB1的同源物，即GNB1—GNB5。RGS1為一GTP酶激活物，其可以與G蛋白三聚物的α亞單位相互作用,激活其活性使GTP發(fā)生水解，從而抑制G蛋白信號通路的轉(zhuǎn)導。盡管只在擬南芥中只有一個RGS蛋白，但是，在人中卻有20個左右的RGS蛋白。在這些蛋白中，RGS5與擬南芥中的RGS1的序列最相似，因而用于進一步的實驗驗證。通過免疫共沉淀實驗和His-pulldown實驗，我們發(fā)現(xiàn)RGS5可以與NDRG2相互作用。為了建立一種可以預測某一蛋白相互作用分子的方法，我們首次聯(lián)合基因表達譜數(shù)據(jù)和蛋白質(zhì)序列特征預測了Dusp6的相互作用分子。我們用MINDy算法來發(fā)現(xiàn)Dusp6的調(diào)節(jié)蛋白，用Pred_PPI來提高預測的準確性。通過這一方法，，我們成功預測了Mapk8為Dusp6的相互作用分子。 總之，通過數(shù)據(jù)挖掘和實驗驗證的結(jié)合，我們成功建立了一種可以用來研究某一特定基因的轉(zhuǎn)錄調(diào)控和其參與的信號轉(zhuǎn)導的策略。由于這些方法節(jié)省時間和資源，我們期望它們將來被用于其它基因的研究當中。
[Abstract]:In recent years, the application of high-throughput technology in biomedical research has led to the accumulation of a large number of biological data, including gene and protein sequences, DNA microarrays and biomedical images. In our research, we used data mining technology to extract effective information from HepG2 cell expression profiles chip for the first time, and innovatively predicted the transcriptional regulatory factors of NDRG2 and the phase of NDRG2 and Dusp6. Interaction molecules.
Because the expression of NDRG2 in tumor cells is decreased, in order to understand the biological effect of NDRG2 on tumor cells, we detected the gene expression of HepG2 cells with expression profiling chip, and analyzed the enrichment of the chip data. GO biological process analysis showed that the expression of genes involved in G protein signal transduction increased. Five of these genes were identified by qRT-PCR, while the genes involved in M phase were decreased, which was consistent with the analysis of cell cycle. Signal pathway analysis showed that the expression of genes related to blood cell differentiation and cell adhesion increased significantly, and the expression of genes related to protein GPI modification, protein degradation and cell secretion decreased. We found that NDRG2 could increase the phosphorylation level of p38 through the analysis of motifs and experiments. Through enrichment analysis, we successfully extracted effective information from the chip data and provided a molecular basis for understanding the mechanism of NDRG2 in tumor cells.
In order to understand the expression pattern of NDRG2 under different conditions, we used ARACNE algorithm and phantom scan to predict the transcription factors that regulate the expression of NDRG2. Through phantom scan, we found that there were 129 binding sites of transcription factors in the promoter region of NDRG2. Finally, we obtained 53 candidate transcription factors that might regulate the expression of NDRG2 gene. Among these transcription factors, KLF4 was chosen to induce colon cancer cells to differentiate. Functional analysis of these transcription factors showed that they were mainly related to cell differentiation and organogenesis. The transport and localization of substances in cells are consistent with previous studies.
Finally, in order to find the interaction molecules of NDRG2, we searched for the homologues of NDRG2 in Arabidopsis and identified NDL1, NDL2 and NDL3 as the homologous proteins of NDRG2. These NDL proteins have been reported to interact with AGB1 and RGS1, suggesting that NDRG2 can interact with the homologues of these two molecules in humans. AGB1 is a G protein trimer. In humans, five AGB1 homologues, GNB1-GNB5.RGS1, are GTP enzyme activators that interact with the alpha subunit of G-protein trimer, activate its activity to hydrolyze GTP and thus inhibit the G-protein signaling pathway. Although there is only one RGS protein in Arabidopsis, there are about 20 in humans. RGS protein. Among these proteins, RGS5 is the most similar to RGS1 in Arabidopsis and is therefore used for further experimental verification. Through immunoprecipitation and his-pulldown experiments, we found that RGS5 can interact with NDRG2. To establish a method for predicting a protein-protein interaction molecule, we first combined the bases. Interacting molecules of Dusp6 were predicted based on the expression profile data and protein sequence characteristics. We used MINDy algorithm to find the regulatory proteins of Dusp6, and used Pred_PPI to improve the accuracy of prediction.
In conclusion, by combining data mining with experimental verification, we have successfully developed a strategy that can be used to study the transcriptional regulation and signal transduction involved in a particular gene.
【學位授予單位】：第四軍醫(yī)大學
【學位級別】：博士
【學位授予年份】：2012
【分類號】：R363

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