藉由大數據挖掘和全基因組識別來研究EB病毒感染人類B淋巴細胞的全基因組之跨物種基因和表觀遺傳基因網路並探查其感染分子機制

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研究生：	鄭博仁 Jheng, Bo Ren
論文名稱：	藉由大數據挖掘和全基因組識別來研究EB病毒感染人類B淋巴細胞的全基因組之跨物種基因和表觀遺傳基因網路並探查其感染分子機制 Investigating the Genome-wide Interspecies Genetic- and Epigenetic- Networks and the Molecular Mechanisms for Human B Lymphocytes Infected with Epstein-Barr Virus via Big Data Mining and Genome-wide Identification
指導教授：	陳博現 Chen, Bor-Sen
口試委員:	蔡錦華王慧菁鄭世進藍忠昱
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電機工程學系 Department of Electrical Engineering
論文出版年：	2017
畢業學年度：	105
語文別：	英文
論文頁數：	93
中文關鍵詞：	艾巴氏貝爾病毒、人類皰疹病毒第四型、人類B淋巴細胞、病毒顆粒生產、通訊分子機制、物種間基因和表觀遺傳基因網路、主成份網路投影、潛在藥物標靶、多分子藥物
外文關鍵詞：	Epstein-Barr Virus, human herpesvirus 4, human B lymphocytes, virion production, cross-talk molecular mechanism, interspecies genetic- and epigenetic- network, principal network projection (PNP), potential drug target, multi-molecule drug
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Epstein-Barr病毒(EBV)也稱為人類皰疹病毒第四型(HHV-4)，普遍存在於全世界的所有人口，EB病毒主要感染人類B淋巴細胞和上皮細胞，因此他和這些細胞相關的多種惡性腫瘤有關連。在這篇研究中，我們想要建構出物種間的通訊網路來探討在EBV感染期間的第一感染階段(0~24小時)和第二感染階段(8~72小時)，宿主B細胞和EB病毒之間的分子機制。我們首先透過大數據資料庫挖掘，來建立一個候選全基因組物種間基因和表觀遺傳基因的網路(候選GIGEN)，接著我們藉由他們相對應的次世代定序(NGS)數據，以及透過動態交互作用模型、系統識別方法、系統階層測定方法，在候選GIGEN內刪除偽陽性來獲得在裂解週期第一和第二感染階段的真實GIGEN。GIGEN中包含蛋白質間交互作用網路(PPINs)、基因/微小RNA/長鏈非編碼RNA的調控網路(GRNs)，以及宿主病毒間通訊網路，由於GIGEN仍然非常複雜，因此為了增加對EBV感染時的通訊分子機制有更深入的理解，我們藉由主成份網路投影方法(PNP)從GIGEN中提取出核心的GIGEN，包含宿主病毒間核心網路(HVCNs)和宿主病毒間核心生物途徑(HVCPs)。
以這些識別後的結果為基礎，我們發現EBV會先利用病毒蛋白和miRNA去抑制和表觀遺傳相關的人類蛋白或基因的活性，接著可能會去劫持表觀遺傳調控的功能使得人類免疫反應失調，此外，病毒蛋白EBNA2和Zta在EBV裂解週期的初始化扮演主要的角色，並且認為這兩個蛋白是潛在的藥物標靶，EBNA2有效的上調控有參與受感染細胞增生以及存活的基因來逃避人類的免疫攻擊，此外，立即早期裂解基因產物Zta是一個轉錄因子，他能夠誘導完整的EBV裂解基因表現程序。另外，EBV膜蛋白LMP2B藉由病毒BLLF2來和LMP1相互合作，能增強人類B細胞的活性以及有利於病毒顆粒的生產和運輸，而EBV核抗原EBNA1對於EBV藉由抗凋亡來幫助病毒顆粒複製生產是關鍵因子，因此，這些病毒蛋白可以被預測為潛在的藥物標靶。最後，我們提出了幾種多分子藥物，其中包含百里香醌(TQ)、丙戊醯胺(VPM)和澤布拉林(Zeb)，藉此來標靶藥物目標做為治療性干預的方法，並且能作為對EBV相關的惡性腫瘤的抑制劑。

Epstein-Barr Virus (EBV), also called as human herpesvirus 4 (HHV-4), is prevalent in all human populations. EBV mainly infects human B lymphocytes and epithelial cells, so it is associated with the various malignancies about them. In this study, we want to construct the interspecies networks to investigate the cross-talk molecular mechanisms between human B cells and EBV at the first infection stage (0~24 hours) and at the second infection stage (8~72 hours) during the EBV infection, respectively. We first construct a candidate genome-wide interspecies genetic- and epigenetic- network (candidate GIGEN) through big databases mining. Then we prune the false positives in the candidate GIGEN to obtain the real GIGENs at the first and second infection stage in the lytic phase by their corresponding NGS data through the dynamic interaction models, the system identification approach, and the system order detection method. The GIGEN consists of protein-protein interaction networks (PPINs), gene/miRNA/lncRNA regulation networks (GRNs), host-virus cross-talk networks. Since the GIGENs are still very complex. In order to gain an insight into the cross-talk molecular mechanisms of the EBV infection, the core GIGENs including host-virus core networks (HVCNs) and host-virus core pathways (HVCPs) are extracted from GIGENs by the principal network projection (PNP) method.
On the basis of these identified results, we found that EBV can exploit viral proteins and miRNAs to inhibit the activities of the epigenetics-associated human proteins or genes at first, and then may hijack the functions of the epigenetic regulations to make human immune responses dysregulated. Moreover, viral proteins EBNA2 and Zta play the primary role in the initiation of EBV lytic phase and could be considered as the potential drug targets. EBNA2 is efficient in upregulating genes involving in the infected cell proliferation and survival to evade human immune attacks. Besides, the immediate-early lytic gene product, Zta, is a transcription factor able to induce the entire program of the EBV lytic gene expression. Additionally, EBV membrane protein LMP2B works in cooperation with LMP1 via viral BLLF2 to enhance the activity of human B cells and facilitate the production and transportation of the viral particles, and EBV nuclear antigen EBNA1 is crucial for EBV to reproduce via anti-apoptosis; thus, these viral proteins could be suggested as the potential drug targets. Eventually, we proposed the multi-molecule drugs composed of Thymoquinone (TQ), Valpromide (VPM), and Zebularine (Zeb) to target the drug targets for the therapeutic intervention as the inhibitors of the EBV-associated malignancies.

誌謝    I
摘要    II
Abstract    IV
Contents    V
List of Tables    VII
List of Figures    VIII
List of abbreviations    IX
Chapter 1. Introduction    1
Chapter 2. Materials and Methods    5
2.1    Overview of the construction for interspecies GIGENs in human B cells infected with EBV during the lytic production phase    5
2.2    Big data mining and data preprocessing of NGS data for human and EBV and methylation data for human    5
2.3    Dynamic models of the interspecies GIGENs for human B cells and EBV during the lytic infection process    7
2.4    System identification approach of the dynamic models of GIGENs    12
2.5    System order detection scheme of the dynamic models of GIGENs    26
2.6    Extracting core network from the real interspecies GIGEN by using the PNP method    30
Chapter 3. Results    35
3.1    GIGENs of the first and the second infection stage in the lytic phase of B cells infected with EBV    35
3.2    HVCNs at the first and second infection stage in the lytic phase of B cells infected with EBV    36
3.2.1    The significant cellular processes of the HVCNs in the lytic replication cycle    36
3.2.2    The intracellular signaling pathways in HVCNs modified by the epigenetic regulation during the lytic infection    37
3.3    HVCPs at the first and second infection stage during the lytic replication cycle    38
3.3.1    The new virion production through host-virus cross-talk interactions at the first infection stage    38
3.3.2    The transportation process of viral particles through host-virus cross-talk interactions at the second infection stage    49
3.3.3    Overview of the lytic infection molecular mechanism from the first to second infection stage in human B cells infected with EBV    55
3.4    Drug target proteins and multi-molecule drug design    58
Chapter 4. Discussion    61
Chapter 5. Conclusion    64
Reference    88

                                

1. Gru, A., et al., The Epstein-Barr virus (EBV) in T cell and NK cell lymphomas: time for a reassessment. Current hematologic malignancy reports, 2015. 10(4): p. 456-467.
2. Odumade, O.A., K.A. Hogquist, and H.H. Balfour, Progress and problems in understanding and managing primary Epstein-Barr virus infections. Clinical microbiology reviews, 2011. 24(1): p. 193-209.
3. Murata, T. and T. Tsurumi, Switching of EBV cycles between latent and lytic states. Reviews in medical virology, 2014. 24(3): p. 142-153.
4. Hong, G.K., et al., The BRRF1 early gene of Epstein-Barr virus encodes a transcription factor that enhances induction of lytic infection by BRLF1. Journal of virology, 2004. 78(10): p. 4983-4992.
5. Murata, T., Regulation of Epstein–Barr virus reactivation from latency. Microbiology and immunology, 2014. 58(6): p. 307-317.
6. Kenney, S.C. and J.E. Mertz, Regulation of the latent-lytic switch in Epstein-Barr virus. Seminars in Cancer Biology, 2014. 26: p. 60-68.
7. Hammerschmidt, W. and B. Sugden, Genetic analysis of immortalizing functions of Epstein Barr virus in human B lymphocytes. Nature, 1989. 340(6232): p. 393-397.
8. Nowag, H., et al., Macroautophagy proteins assist Epstein Barr virus production and get incorporated into the virus particles. EBioMedicine, 2014. 1(2): p. 116-125.
9. Tempera, I. and P.M. Lieberman, Epigenetic regulation of EBV persistence and oncogenesis. Seminars in Cancer Biology, 2014. 26: p. 22-29.
10. O'Grady, T., et al., Global bidirectional transcription of the Epstein-Barr virus genome during reactivation. Journal of virology, 2014. 88(3): p. 1604-1616.
11. Kalla, M., C. Gobel, and W. Hammerschmidt, The Lytic Phase of Epstein-Barr Virus Requires a Viral Genome with 5-Methylcytosine Residues in CpG Sites. Journal of Virology, 2012. 86(1): p. 447-458.
12. Oughtred, R., et al., BioGRID: A Resource for Studying Biological Interactions in Yeast. Cold Spring Harbor Protocols, 2016. 2016(1): p. pdb. top080754.
13. Xenarios, I., et al., DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions. Nucleic acids research, 2002. 30(1): p. 303-305.
14. Bader, G.D., D. Betel, and C.W. Hogue, BIND: the biomolecular interaction network database. Nucleic acids research, 2003. 31(1): p. 248-250.
15. Kerrien, S., et al., IntAct—open source resource for molecular interaction data. Nucleic acids research, 2007. 35(suppl 1): p. D561-D565.
16. Chatr-Aryamontri, A., et al., VirusMINT: a viral protein interaction database. Nucleic acids research, 2009. 37(suppl 1): p. D669-D673.
17. Bovolenta, L.A., M.L. Acencio, and N. Lemke, HTRIdb: an open-access database for experimentally verified human transcriptional regulation interactions. BMC genomics, 2012. 13(1): p. 405.
18. Zheng, G., et al., ITFP: an integrated platform of mammalian transcription factors. Bioinformatics, 2008. 24(20): p. 2416-2417.
19. Friard, O., et al., CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC bioinformatics, 2010. 11(1): p. 435.
20. Calderone, A., L. Licata, and G. Cesareni, VirusMentha: a new resource for virus-host protein interactions. Nucleic acids research, 2014: p. gku830.
21. Mei, S. and K. Zhang, Computational discovery of Epstein-Barr virus targeted human genes and signalling pathways. Scientific Reports, 2016. 6: p. 30612.
22. Orchard, S., et al., Protein interaction data curation: the International Molecular Exchange (IMEx) consortium. Nature methods, 2012. 9(4): p. 345-350.
23. del-Toro, N., et al., A new reference implementation of the PSICQUIC web service. Nucleic acids research, 2013. 41(W1): p. W601-W606.
24. Qureshi, A., et al., VIRmiRNA: a comprehensive resource for experimentally validated viral miRNAs and their targets. Database, 2014. 2014: p. bau103.
25. Li, Y., et al., ViRBase: a resource for virus–host ncRNA-associated interactions. Nucleic acids research, 2014: p. gku903.
26. Xiao, F., et al., miRecords: an integrated resource for microRNA–target interactions. Nucleic acids research, 2009. 37(suppl 1): p. D105-D110.
27. Li, J.-H., et al., starBase v2. 0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic acids research, 2013: p. gkt1248.
28. Hsu, S.-D., et al., miRTarBase: a database curates experimentally validated microRNA–target interactions. Nucleic acids research, 2010: p. gkq1107.
29. Hernando, H., et al., The B cell transcription program mediates hypomethylation and overexpression of key genes in Epstein-Barr virus-associated proliferative conversion. Genome biology, 2013. 14(1): p. 1.
30. Chen, B.-S. and C.-W. Li, Constructing an integrated genetic and epigenetic cellular network for whole cellular mechanism using high-throughput next-generation sequencing data. BMC systems biology, 2016. 10(1): p. 1.
31. Li, C.-W., Y.-L. Lee, and B.-S. Chen, Genetic-and-Epigenetic Interspecies Networks for Cross-Talk Mechanisms in Human Macrophages and Dendritic Cells during MTB Infection. Frontiers in Cellular and Infection Microbiology, 2016. 6.
32. Smith, Z.D. and A. Meissner, DNA methylation: roles in mammalian development. Nature Reviews Genetics, 2013. 14(3): p. 204-220.
33. Lu, P., et al., Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nature biotechnology, 2007. 25(1): p. 117-124.
34. Li, C.W., Y.L. Lee, and B.S. Chen, Genetic-and-Epigenetic Interspecies Networks for Cross-Talk Mechanisms in Human Macrophages and Dendritic Cells during MTB Infection. Frontiers in Cellular and Infection Microbiology, 2016. 6.
35. Wang, Y.-C., et al., Interspecies protein-protein interaction network construction for characterization of host-pathogen interactions: a Candida albicans-zebrafish interaction study. BMC systems biology, 2013. 7(1): p. 1.
36. Wang, Y.-C., et al., Prediction of phenotype-associated genes via a cellular network approach: a Candida albicans infection case study. PloS one, 2012. 7(4): p. e35339.
37. Hsu, C.-Y., et al., Systematic approach to Escherichia coli cell population control using a genetic lysis circuit. BMC systems biology, 2014. 8(Suppl 5): p. S7.
38. Shannon, P., et al., Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 2003. 13(11): p. 2498-2504.
39. Li, C.-W., W.-H. Wang, and B.-S. Chen, Investigating the specific core genetic-and-epigenetic networks of cellular mechanisms involved in human aging in peripheral blood mononuclear cells. Oncotarget, 2016. 7(8): p. 8556-8579.
40. Huang, D.W., B.T. Sherman, and R.A. Lempicki, Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Research, 2009. 37(1): p. 1-13.
41. Granato, M., et al., EBV blocks the autophagic flux and appropriates the autophagic machinery to enhance viral replication. Journal of virology, 2014: p. JVI. 02199-14.
42. Calderwood, M.A., et al., Epstein-Barr virus and virus human protein interaction maps. Proceedings of the National Academy of Sciences of the United States of America, 2007. 104(18): p. 7606-7611.
43. Albanese, M., et al., Epstein-Barr virus microRNAs reduce immune surveillance by virus-specific CD8(+) T cells. Proceedings of the National Academy of Sciences of the United States of America, 2016. 113(42): p. E6467-E6475.
44. Hatton, O.L., et al., The interplay between Epstein–Barr virus and B lymphocytes: implications for infection, immunity, and disease. Immunologic research, 2014. 58(2-3): p. 268-276.
45. Söllner, J., et al., Concept and application of a computational vaccinology workflow. Immunome research, 2010. 6(2): p. 1.
46. Nakamura, Y., et al., The GAS5 (growth arrest-specific transcript 5) gene fuses to BCL6 as a result of t (1; 3)(q25; q27) in a patient with B-cell lymphoma. Cancer genetics and cytogenetics, 2008. 182(2): p. 144-149.
47. Zhao, L., et al., Long non-coding RNA SNHG5 suppresses gastric cancer progression by trapping MTA2 in the cytosol. Oncogene, 2016.
48. Zhang, Y., et al., Association between RNF41 gene c.-206 T> A genetic polymorphism and risk of congenital heart diseases in the Chinese Mongolian population. Genetics and molecular research: GMR, 2016. 15(2).
49. Wauman, J., et al., RNF41 (Nrdp1) controls type 1 cytokine receptor degradation and ectodomain shedding. J Cell Sci, 2011. 124(6): p. 921-932.
50. Rowe, M., S. Raithatha, and C. Shannon-Lowe, Counteracting effects of cellular Notch and Epstein-Barr virus EBNA2: implications for stromal effects on virus-host interactions. Journal of virology, 2014. 88(20): p. 12065-12076.
51. Choy, E.Y.-W., et al., An Epstein-Barr virus–encoded microRNA targets PUMA to promote host cell survival. The Journal of experimental medicine, 2008. 205(11): p. 2551-2560.
52. Meckes Jr, D. and N. Raab-Traub, Mining Epstein-Barr Virus LMP1 Signaling Networks. J Carcinogene Mutagene S, 2011. 11: p. 37-39.
53. Zeng, L., et al., Cellular FLICE-like Inhibitory Protein (c-FLIP) and PS1-associated Protein (PSAP) Mediate Presenilin 1-induced γ-Secretase-dependent and-independent Apoptosis, Respectively. Journal of Biological Chemistry, 2015. 290(30): p. 18269-18280.
54. Li, X. and S. Bhaduri-McIntosh, A Central Role for STAT3 in Gammaherpesvirus-Life Cycle and-Diseases. Frontiers in Microbiology, 2016. 7.
55. Jochum, S., et al., The EBV immunoevasins vIL-10 and BNLF2a protect newly infected B cells from immune recognition and elimination. PLoS Pathog, 2012. 8(5): p. e1002704.
56. Kamperschroer, C., et al., The genomic sequence of lymphocryptovirus from cynomolgus macaque. Virology, 2016. 488: p. 28-36.
57. Sides, M.D., et al., Arsenic mediated disruption of promyelocytic leukemia protein nuclear bodies induces ganciclovir susceptibility in Epstein–Barr positive epithelial cells. Virology, 2011. 416(1): p. 86-97.
58. Sivachandran, N., J.Y. Cao, and L. Frappier, Epstein-Barr virus nuclear antigen 1 hijacks the host kinase CK2 to disrupt PML nuclear bodies. Journal of virology, 2010. 84(21): p. 11113-11123.
59. Lai, K.W., et al., MicroRNA-130b regulates the tumour suppressor RUNX3 in gastric cancer. European Journal of Cancer, 2010. 46(8): p. 1456-1463.
60. Hsu, D.-H., et al., Expression of interleukin-10 activity by Epstein-Barr virus protein BCRF1. Science, 1990. 250(4982): p. 830.
61. Han, L., et al., Sequence variation of Epstein-Barr virus (EBV) BCRF1 in lymphomas in non-endemic areas of nasopharyngeal carcinoma. Archives of virology, 2015. 160(2): p. 441-445.
62. Park, G.B., et al., Melphalan-induced apoptosis of EBV-transformed B cells through upregulation of TAp73 and XAF1 and nuclear import of XPA. The Journal of Immunology, 2013. 191(12): p. 6281-6291.
63. Koganti, S., et al., Cellular STAT3 functions via PCBP2 to restrain Epstein-Barr virus lytic activation in B lymphocytes. Journal of virology, 2015. 89(9): p. 5002-5011.
64. Seo, J., et al., Cell cycle arrest and lytic induction of EBV-Transformed B lymphoblastoid cells by a histone deacetylase inhibitor, Trichostatin A. Oncology reports, 2008. 19(1): p. 93.
65. Ahsan, N., et al., Epstein-Barr virus transforming protein LMP1 plays a critical role in virus production. Journal of virology, 2005. 79(7): p. 4415-4424.
66. Jung, E.J., et al., Lytic induction and apoptosis of Epstein‐Barr virus-associated gastric cancer cell line with epigenetic modifiers and ganciclovir. Cancer letters, 2007. 247(1): p. 77-83.
67. Jones, K., et al., Sodium valproate in combination with ganciclovir induces lysis of EBV‐infected lymphoma cells without impairing EBV‐specific T‐cell immunity. International journal of laboratory hematology, 2010. 32(1p1): p. e169-e174.
68. Kenney, S.C., Reactivation and lytic replication of EBV. 2007.
69. Hutajulu, S.H., et al., Therapeutic implications of Epstein-Barr virus infection for the treatment of nasopharyngeal carcinoma. Ther Clin Risk Manag, 2014. 10(September): p. 721-736.
70. Noh, K.W., J. Park, and M.S. Kang, Targeted disruption of EBNA1 in EBV-infected cells attenuated cell growth. Bmb Reports, 2016. 49(4): p. 226-231.
71. Zihlif, M.A., et al., Thymoquinone Efficiently Inhibits the Survival of EBV-Infected B Cells and Alters EBV Gene Expression. Integrative cancer therapies, 2013. 12(3): p. 257-263.
72. Gorres, K.L., et al., Valpromide Inhibits Lytic Cycle Reactivation of Epstein-Barr Virus. mBio, 2016. 7(2): p. e00113-16.
73. Rao, S.P., et al., Zebularine reactivates silenced E-cadherin but unlike 5-Azacytidine does not induce switching from latent to lytic Epstein-Barr virus infection in Burkitt's lymphoma Akata cells. Molecular cancer, 2007. 6(1): p. 1.
74. Zhu, Y., et al., γ-Herpesvirus-encoded miRNAs and their roles in viral biology and pathogenesis. Current opinion in virology, 2013. 3(3): p. 266-275.
75. Alberghini, F., et al., An epigenetic view of B-cell disorders. Immunology and cell biology, 2015. 93(3): p. 253-260.
76. Dreyfus, D.H., Gene sharing between Epstein–Barr virus and human immune response genes. Immunologic Research, 2016: p. 1-9.

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