DNAzymes针对Ezrin mRNA的反义技术靶点筛选及验证
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摘要
目的分析肿瘤远处转移相关蛋白(Ezrin mRNA)的结构,寻找并验证DNAzymes作用的最佳靶点。方法利用RNAstructure与RNAdraw程序分析Ezrin mRNA结构,计算其一、二级结构,两种程序同时计算出碱基未配对的单链成环区,且连续存在4个以上,则将其设为反义技术的靶区域,在此区域内设计DNAzymes的作用靶点,再依据最低自由能原则,运用计算机中的OligoWalk程序进行筛选,以此方式得到各反义技术的作用靶点,以实验方法验证预测结果。结果两种软件预测的共同的单链区共42个,其中完全匹配的单链区21个,编码区具27个。AU1655、AU1751、AU1766、AU1789及GU2623位于连续未配对碱基超过10个的单链区,仅AU1655、AU1751、AU1766、AU1789符合要求。酶切反应结果显示DNAzymes在AU1751位点能够最为理想地切割Ezrin m RNA。结论相对于传统的单纯依靠实验来寻找靶点,核酸二级结构联合热动力学参数能够更精确、快速地处理靶点的设计和选取问题。AU1751位点相对应的DNAzymes不易形成稳定的自身杂合体,有利于DNAzymes结合RNA。
Objective To analyze the structure of distant metastasis associated protein(Ezrin m RNA) and find and verify the best target of DNAzymes. Methods RNAstructure and RNAdraw programs were used to analyze the structure of Ezrin mRNA and calculate its first or secondary structure. If RNAstructure and RNAdraw simultaneously calculate 4 or more unpaired single chain ring forming regions, the single chain ring forming region would be set as the target area of antisense technology for the design of the target of the DNAzymes. Then, according to the principle of minimum free energy, the OligoWalk program was used for screening, and the target of each antisense technology was screened by screening. The experimental method was used to verify the prediction results. Results There were 42 common single chain regions predicted by the two software, of which 21 were single matched, and 27 were coding regions. AU1655,AU1751, AU1766, AU1789 and GU2623 were located in the single chain region over 10 consecutive unpaired bases.Only AU1655, AU1751, AU1766 and AU1789 meet the requirements. The results of enzyme digestion showed that DNAzymes could cut Ezrin mRNA most ideally at AU1751 site. Conclusion Compared with the traditional experiment to find the target, the combined thermal dynamic parameters of the two stage structure of nucleic acid could deal with the design and selection of the target more accurately and quickly. The DNAzymes corresponding to the AU1751 locus is less likely to form stable self heterozygotes, which is beneficial to DNAzymes binding to RNA.
Objective To analyze the structure of distant metastasis associated protein(Ezrin m RNA) and find and verify the best target of DNAzymes. Methods RNAstructure and RNAdraw programs were used to analyze the structure of Ezrin mRNA and calculate its first or secondary structure. If RNAstructure and RNAdraw simultaneously calculate 4 or more unpaired single chain ring forming regions, the single chain ring forming region would be set as the target area of antisense technology for the design of the target of the DNAzymes. Then, according to the principle of minimum free energy, the OligoWalk program was used for screening, and the target of each antisense technology was screened by screening. The experimental method was used to verify the prediction results. Results There were 42 common single chain regions predicted by the two software, of which 21 were single matched, and 27 were coding regions. AU1655,AU1751, AU1766, AU1789 and GU2623 were located in the single chain region over 10 consecutive unpaired bases.Only AU1655, AU1751, AU1766 and AU1789 meet the requirements. The results of enzyme digestion showed that DNAzymes could cut Ezrin mRNA most ideally at AU1751 site. Conclusion Compared with the traditional experiment to find the target, the combined thermal dynamic parameters of the two stage structure of nucleic acid could deal with the design and selection of the target more accurately and quickly. The DNAzymes corresponding to the AU1751 locus is less likely to form stable self heterozygotes, which is beneficial to DNAzymes binding to RNA.
引文
[1]Tsukita S,Yonemura S,Tsukita S.Proteins:head-to-tail regulation of actin-plasma membrane interation[J].Trends Biochem Sci,1997,22(2):53-58.
[2]Khanna C,Khan J,Nguyen P,et al.Metastasis-associated differences in gene expression in a murine model of osteosarcoma[J].Cancer Res,2001,61(9):3750-3759.
[3]Passacantilli I,Frisone P,De Paola E,et al.hnRNPMguides an alternative splicing program in response to inhibition of the PI3K/AKT/mTOR pathway in Ewing sarcoma cells[J].Nucleic Acids Res,2017,45(21):12 270-12 284.doi:10.1093/nar/gkx831.
[4]Cash T,Yin H,McCracken C,et al.Correlation of Ezrin Expression Pattern and Clinical Outcomes in Ewing Sarcoma[J].Sarcoma,2017,2017:8758623.doi:10.1155/2017/8758623.
[5]Rouven Brückner B,Pietuch A,Nehls S,et al.Ezrin is a Major Regulator of Membrane Tension in Epithelial Cells[J].Sci Rep,2015,5:14700.doi:10.1038/srep14700.
[6]Huang L,Qin Y,Zuo Q,et al.Ezrin mediates both HGF/Met autocrine and non-autocrine signaling-induced metastasis in melanoma[J].Int J Cancer,2018,142(8):1652-1663.doi:10.1002/ijc.31196.
[7]Cihan YB.Does ezrin play a predictive role in cancer patients undergoing radiotherapy and/or chemotherapy?[J].Hum Pathol,2018,22.pii:S0046-8177(18)30226-0.
[8]张洪,张阳德.端粒酶反义技术治疗恶性肿瘤的研究动态[J].中国医学工程,2006,14(6):606-610.doi:10.3969/j.issn.1672-2019.2006.06.013.
[9]Wang F,Lu CH,Willner I.From cascaded catalytic nucleic acids to enzyme-DNA nanostructures:controlling reactivity,sensing,logic operations,and assembly of complex structures[J].Chem Rev,2014,114(5):2881-941.doi:10.1021/cr400354z.
[10]Danaee P,Rouches M,Wiley M,et al.bpRNA:large-scale automated annotation and analysis of RNA secondary structure[J].Nucleic Acids Res,2018,46(11):5381-5394.doi:10.1093/nar/gky285.
[11]He S,Mao X,Sun H,et al.Potential therapeutic targets in the process of nucleic acid recognition:opportunities and challenges[J].Trends Pharmacol Sci,2015,36(1):51-64.
[12]Kruspe S,Giangrande PH.Aptamer-siRNA Chimeras:Discovery,Progress,and Future Prospects[J].Biomedicines,2017,5(3).pii:E45.
[13]Lugowska I,Mierzejewska E,Lenarcik M,et al.The clinical significance of changes in ezrin expression in osteosarcoma of children and young adults[J].Tumour Biol,2016,37(9):12 071-12 078.
[14]Yu Y,Khan J,Khanna C,et al.Expression profiling identifies the cytoskeletal organizer ezrin and the developmental homeoprotein Six-1 as key metastatic regulators[J].Nat Med,2004,10(2):175-181.
[15]Maus MK,Hanna DL,Stephens CL,et al.Distinct gene expression profiles of proximal and distal colorectal cancer:implications for cytotoxic and targeted therapy[J].Pharmacogenomics J,2015,15(4):354-362.doi:10.1038/tpj.2014.73.
[16]Pilsl M,Crucifix C,Papai G,et al.Structure of the initiation-competent RNA polymerase I and its implication for transcription[J].Nat Commun,2016,7:12126.doi:10.1038/ncomms12126.
[17]Glouzon JS,Ouangraoua A.aliFreeFold:an alignmentfree approach to predict secondary structure from homologous RNA sequences[J].Bioinformatics,2018,34(13):i70-i78.doi:10.1093/bioinformatics/bty234.
[18]Zhu Y,Xie Z,Li Y,et al.Research on folding diversity in statistical learning methods for RNA secondary structure prediction[J].Int J Biol Sci,2018,14(8):872-882.doi:10.7150/ijbs.24595.
[19]Zhao JJ,Lemke G.Rules for ribozymes[J].Mol Cell Neurosci,1998,11(1-2):92-97.
[2]Khanna C,Khan J,Nguyen P,et al.Metastasis-associated differences in gene expression in a murine model of osteosarcoma[J].Cancer Res,2001,61(9):3750-3759.
[3]Passacantilli I,Frisone P,De Paola E,et al.hnRNPMguides an alternative splicing program in response to inhibition of the PI3K/AKT/mTOR pathway in Ewing sarcoma cells[J].Nucleic Acids Res,2017,45(21):12 270-12 284.doi:10.1093/nar/gkx831.
[4]Cash T,Yin H,McCracken C,et al.Correlation of Ezrin Expression Pattern and Clinical Outcomes in Ewing Sarcoma[J].Sarcoma,2017,2017:8758623.doi:10.1155/2017/8758623.
[5]Rouven Brückner B,Pietuch A,Nehls S,et al.Ezrin is a Major Regulator of Membrane Tension in Epithelial Cells[J].Sci Rep,2015,5:14700.doi:10.1038/srep14700.
[6]Huang L,Qin Y,Zuo Q,et al.Ezrin mediates both HGF/Met autocrine and non-autocrine signaling-induced metastasis in melanoma[J].Int J Cancer,2018,142(8):1652-1663.doi:10.1002/ijc.31196.
[7]Cihan YB.Does ezrin play a predictive role in cancer patients undergoing radiotherapy and/or chemotherapy?[J].Hum Pathol,2018,22.pii:S0046-8177(18)30226-0.
[8]张洪,张阳德.端粒酶反义技术治疗恶性肿瘤的研究动态[J].中国医学工程,2006,14(6):606-610.doi:10.3969/j.issn.1672-2019.2006.06.013.
[9]Wang F,Lu CH,Willner I.From cascaded catalytic nucleic acids to enzyme-DNA nanostructures:controlling reactivity,sensing,logic operations,and assembly of complex structures[J].Chem Rev,2014,114(5):2881-941.doi:10.1021/cr400354z.
[10]Danaee P,Rouches M,Wiley M,et al.bpRNA:large-scale automated annotation and analysis of RNA secondary structure[J].Nucleic Acids Res,2018,46(11):5381-5394.doi:10.1093/nar/gky285.
[11]He S,Mao X,Sun H,et al.Potential therapeutic targets in the process of nucleic acid recognition:opportunities and challenges[J].Trends Pharmacol Sci,2015,36(1):51-64.
[12]Kruspe S,Giangrande PH.Aptamer-siRNA Chimeras:Discovery,Progress,and Future Prospects[J].Biomedicines,2017,5(3).pii:E45.
[13]Lugowska I,Mierzejewska E,Lenarcik M,et al.The clinical significance of changes in ezrin expression in osteosarcoma of children and young adults[J].Tumour Biol,2016,37(9):12 071-12 078.
[14]Yu Y,Khan J,Khanna C,et al.Expression profiling identifies the cytoskeletal organizer ezrin and the developmental homeoprotein Six-1 as key metastatic regulators[J].Nat Med,2004,10(2):175-181.
[15]Maus MK,Hanna DL,Stephens CL,et al.Distinct gene expression profiles of proximal and distal colorectal cancer:implications for cytotoxic and targeted therapy[J].Pharmacogenomics J,2015,15(4):354-362.doi:10.1038/tpj.2014.73.
[16]Pilsl M,Crucifix C,Papai G,et al.Structure of the initiation-competent RNA polymerase I and its implication for transcription[J].Nat Commun,2016,7:12126.doi:10.1038/ncomms12126.
[17]Glouzon JS,Ouangraoua A.aliFreeFold:an alignmentfree approach to predict secondary structure from homologous RNA sequences[J].Bioinformatics,2018,34(13):i70-i78.doi:10.1093/bioinformatics/bty234.
[18]Zhu Y,Xie Z,Li Y,et al.Research on folding diversity in statistical learning methods for RNA secondary structure prediction[J].Int J Biol Sci,2018,14(8):872-882.doi:10.7150/ijbs.24595.
[19]Zhao JJ,Lemke G.Rules for ribozymes[J].Mol Cell Neurosci,1998,11(1-2):92-97.