請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68025
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 黃念祖(Nien-Tsu Huang) | |
dc.contributor.author | Shu-Hong Huang | en |
dc.contributor.author | 黃舒鴻 | zh_TW |
dc.date.accessioned | 2021-06-17T02:11:25Z | - |
dc.date.available | 2021-02-26 | |
dc.date.copyright | 2018-02-26 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2018-01-13 | |
dc.identifier.citation | References
1. Uzman, A., Molecular biology of the cell (4th ed.): Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., and Walter, P. Biochemistry and Molecular Biology Education, 2003. 31(4): p. 212-214. 2. Alliance, G. and N.Y.M.A.C.G.N.S. Services, Understanding Genetics: A New York, Mid-Atlantic Guide for Patients and Health Professionals. 2009: Genetic Alliance. 3. Schena, M., Microarray Analysis. 2002: Wiley. 4. Jarrett, K., et al., “Sickle cell anemia: tracking down a mutation”: an interactive learning laboratory that communicates basic principles of genetics and cellular biology. Advances in Physiology Education, 2016. 40(1): p. 110-115. 5. Miranda, D.M., M.A. Romano-Silva, and L. De Marco, Single nucleotide polymorphisms (SNPs) and the search for obesity-related genes. Arquivos Brasileiros de Endocrinologia & Metabologia, 2008. 52: p. 577-578. 6. Newton, C.R., et al., Analysis of any point mutation in DNA. The amplification refractory mutation system (ARMS). Nucleic Acids Research, 1989. 17(7): p. 2503-2516. 7. McGuigan, F.E. and S.H. Ralston, Single nucleotide polymorphism detection: allelic discrimination using TaqMan. Psychiatric genetics, 2002. 12(3): p. 133-136. 8. Kim, S. and A. Misra, SNP genotyping: technologies and biomedical applications. Annu. Rev. Biomed. Eng., 2007. 9: p. 289-320. 9. Perkel, J., SNP genotyping: six technologies that keyed a revolution. Nature Methods, 2008. 5(5): p. 447-453. 10. Dobrowolski, S.F. and C.T. Wittwer, High-Resolution Melt Profiling, in Molecular Analysis and Genome Discovery. 2011, John Wiley & Sons, Ltd. p. 81-113. 11. Bibikova, M. and J.-B. Fan, GoldenGate® Assay for DNA Methylation Profiling, in DNA Methylation: Methods and Protocols, J. Tost, Editor. 2009, Humana Press: Totowa, NJ. p. 149-163. 12. Lukacs, G.L., et al., Size-dependent DNA Mobility in Cytoplasm and Nucleus. Journal of Biological Chemistry, 2000. 275(3): p. 1625-1629. 13. Wang, L. and P. Li, Microfluidic DNA microarray analysis: A review. Analytica Chimica Acta, 2011. 687(1): p. 12-27. 14. Liu, J., et al., Enhanced signals and fast nucleic acid hybridization by microfluidic chaotic mixing. Angewandte Chemie, 2006. 118(22): p. 3700-3705. 15. Lee, H.H., et al., Recirculating flow accelerates DNA microarray hybridization in a microfluidic device. Lab on a Chip, 2006. 6(9): p. 1163-1170. 16. Roy, S., J.H. Soh, and Z. Gao, A microfluidic-assisted microarray for ultrasensitive detection of miRNA under an optical microscope. Lab on a Chip, 2011. 11(11): p. 1886-1894. 17. Park, B.H., et al., Integration of sample pretreatment, μPCR, and detection for a total genetic analysis microsystem. Microchimica Acta, 2014. 181(13-14): p. 1655-1668. 18. Stedtfeld, R.D., et al., Static self-directed sample dispensing into a series of reaction wells on a microfluidic card for parallel genetic detection of microbial pathogens. Biomedical microdevices, 2015. 17(5): p. 89. 19. Choi, J.Y., et al., An integrated allele-specific polymerase chain reaction-microarray chip for multiplex single nucleotide polymorphism typing. Lab Chip, 2012. 12(24): p. 5146-54. 20. Vanderhoeven, J., et al., DNA Microarray Enhancement Using a Continuously and Discontinuously Rotating Microchamber. Analytical Chemistry, 2005. 77(14): p. 4474-4480. 21. Zhu, Y., et al., Graphene and graphene oxide: synthesis, properties, and applications. Advanced materials, 2010. 22(35): p. 3906-3924. 22. Hummers, W.S. and R.E. Offeman, Preparation of Graphitic Oxide. Journal of the American Chemical Society, 1958. 80(6): p. 1339-1339. 23. Sharma, D., et al., Insight into the biosensing of graphene oxide: present and future prospects. Arabian Journal of Chemistry, 2016. 9(2): p. 238-261. 24. Manohar, S., et al., Peeling single-stranded DNA from graphite surface to determine oligonucleotide binding energy by force spectroscopy. Nano letters, 2008. 8(12): p. 4365-4372. 25. Park, J.S., et al., Desorption of single-stranded nucleic acids from graphene oxide by disruption of hydrogen bonding. Analyst, 2013. 138(6): p. 1745-1749. 26. Varghese, N., et al., Binding of DNA nucleobases and nucleosides with graphene. ChemPhysChem, 2009. 10(1): p. 206-210. 27. Huang, P.J.J. and J. Liu, DNA‐Length‐Dependent Fluorescence Signaling on Graphene Oxide Surface. Small, 2012. 8(7): p. 977-983. 28. Jennings, T., M. Singh, and G. Strouse, Fluorescent lifetime quenching near d= 1.5 nm gold nanoparticles: probing NSET validity. Journal of the American Chemical Society, 2006. 128(16): p. 5462-5467. 29. Swathi, R. and K. Sebastian, Long range resonance energy transfer from a dye molecule to graphene has (distance)− 4 dependence. The Journal of chemical physics, 2009. 130(8): p. 086101. 30. Lu, C.H., et al., A Graphene Platform for Sensing Biomolecules. Angewandte Chemie International Edition, 2009. 48(26): p. 4785-4787. 31. Balapanuru, J., et al., A Graphene Oxide–Organic Dye Ionic Complex with DNA‐Sensing and Optical‐Limiting Properties. Angewandte Chemie International Edition, 2010. 49(37): p. 6549-6553. 32. Morales-Narváez, E., et al., Simple Förster resonance energy transfer evidence for the ultrahigh quantum dot quenching efficiency by graphene oxide compared to other carbon structures. Carbon, 2012. 50(8): p. 2987-2993. 33. Wang, X., et al., Ultrasensitive and Selective Detection of a Prognostic Indicator in Early‐Stage Cancer Using Graphene Oxide and Carbon Nanotubes. Advanced Functional Materials, 2010. 20(22): p. 3967-3971. 34. He, Y., et al., Low background signal platform for the detection of ATP: when a molecular aptamer beacon meets graphene oxide. Biosensors & bioelectronics, 2011. 29(1): p. 76-81. 35. Dong, H., et al., Fluorescence resonance energy transfer between quantum dots and graphene oxide for sensing biomolecules. Analytical chemistry, 2010. 82(13): p. 5511-5517. 36. He, S., et al., A Graphene Nanoprobe for Rapid, Sensitive, and Multicolor Fluorescent DNA Analysis. Advanced Functional Materials, 2010. 20(3): p. 453-459. 37. Zhang, M., et al., A versatile graphene-based fluorescence 'on/off' switch for multiplex detection of various targets. Biosensors & bioelectronics, 2011. 26(7): p. 3260-3265. 38. Li, J., et al., A power-free microfluidic chip for SNP genotyping using graphene oxide and a DNA intercalating dye. Chemical communications (Cambridge, England), 2013. 49(30): p. 3125-3127. 39. Huang, Y., H.Y. Yang, and Y. Ai, DNA single-base mismatch study using graphene oxide nanosheets-based fluorometric biosensors. Analytical chemistry, 2015. 87(18): p. 9132-9136. 40. Huang, J., et al., Detecting Arbitrary DNA Mutations Using Graphene Oxide and Ethidium Bromide. Analytical Chemistry, 2015. 87(24): p. 12254-12261. 41. Zhao, X.H., et al., Graphene oxide-based biosensor for sensitive fluorescence detection of DNA based on exonuclease III-aided signal amplification. Anal Chim Acta, 2012. 727: p. 67-70. 42. Peng, L., et al., An exonuclease III and graphene oxide-aided assay for DNA detection. Biosens Bioelectron, 2012. 35(1): p. 475-8. 43. Pang, S., et al., A novel sensing strategy for the detection of Staphylococcus aureus DNA by using a graphene oxide-based fluorescent probe. Analyst, 2013. 138(9): p. 2749-54. 44. Wu, W., et al., A graphene oxide-based nano-beacon for DNA phosphorylation analysis. Chem Commun (Camb), 2011. 47(4): p. 1201-3. 45. Liu, F., J.Y. Choi, and T.S. Seo, Graphene oxide arrays for detecting specific DNA hybridization by fluorescence resonance energy transfer. Biosens Bioelectron, 2010. 25(10): p. 2361-5. 46. Gresham, D., et al., Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray. science, 2006. 311(5769): p. 1932-1936. 47. Ferreira, I.D., V.E. Do Rosário, and P.V. Cravo, Real-time quantitative PCR with SYBR Green I detection for estimating copy numbers of nine drug resistance candidate genes in Plasmodium falciparum. Malaria journal, 2006. 5(1): p. 1. 48. Vitzthum, F., et al., A quantitative fluorescence-based microplate assay for the determination of double-stranded DNA using SYBR Green I and a standard ultraviolet transilluminator gel imaging system. Analytical biochemistry, 1999. 276(1): p. 59-64. 49. Kao, P.-C., et al., A bead-based single nucleotide polymorphism (SNP) detection using melting temperature on a microchip. Microfluidics and nanofluidics, 2014. 17(3): p. 477-488. 50. Lee, K., et al., Sensitive and selective label-free DNA detection by conjugated polymer-based microarrays and intercalating dye. Chemistry of Materials, 2008. 20(9): p. 2848-2850. 51. Morales‐Narváez, E. and A. Merkoçi, Graphene Oxide as an Optical Biosensing Platform. Advanced Materials, 2012. 24(25): p. 3298-3308. 52. Kuan, D.-H., et al., A microfluidic device integrating dual CMOS polysilicon nanowire sensors for on-chip whole blood processing and simultaneous detection of multiple analytes. Lab on a Chip, 2016. 16(16): p. 3105-3113. 53. Paredes, J.I., et al., Graphene oxide dispersions in organic solvents. Langmuir : the ACS journal of surfaces and colloids, 2008. 24(19): p. 10560-10564. 54. Otsu, N., A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics, 1979. 9(1): p. 62-66. 55. Lukacs, G.L., et al., Size-dependent DNA mobility in cytoplasm and nucleus. Journal of Biological Chemistry, 2000. 275(3): p. 1625-1629. 56. Erickson, D., D. Li, and U.J. Krull, Modeling of DNA hybridization kinetics for spatially resolved biochips. Analytical biochemistry, 2003. 317(2): p. 186-200. 57. Heule, M. and A. Manz, Sequential DNA hybridisation assays by fast micromixing. Lab on a Chip, 2004. 4(5): p. 506-511. 58. Peterson, E.M., M.W. Manhart, and J.M. Harris, Single-Molecule Fluorescence Imaging of Interfacial DNA Hybridization Kinetics at Selective Capture Surfaces. Analytical chemistry, 2016. 88(2): p. 1345-1354. 59. Bishop, J., S. Blair, and A. Chagovetz, A competitive kinetic model of nucleic acid surface hybridization in the presence of point mutants. Biophysical journal, 2006. 90(3): p. 831-840. 60. Zhang, H., et al., Size-dependent programming of the dynamic range of graphene oxide-DNA interaction-based ion sensors. Analytical chemistry, 2014. 86(8): p. 4047-4051. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68025 | - |
dc.description.abstract | 在結束全人類基因體定序後,科學家發現人與人之間僅有百分之一的序列是不同的,這意味著每個人之間比我們想像的還要相似。然而這百分之一的不同就是每個人在七十多億人口中仍然是獨特的主因,其中在這百分之一的基因變異中,有高達百分之九十是由單核苷酸多型性 (single nucleotide polymorphism, SNP) 所造成,在經過科學化的分析與統計,已經能瞭解大多數單核苷酸多型性變異點對於基因的影響,因此藉由對單核苷酸多型性的檢測我們可以判斷重大疾病的罹病風險 (如:癌症、心腦血管疾病) 或是臨床用藥指標等資訊。但現今多使用大型自動化DNA陣列檢測平臺,其機台價格高昂且需要一天以上的檢測時間,並不利於基因檢測普及化。
因此本論文想開發一自動化檢測平台並結合DNA微陣列以及氧化石墨烯 (graphene oxide, GO) 以檢測單核苷酸多型性,此平台結合了自動化微流體控制以及往復流動以加快DNA微陣列的反應速率;且為了提升DNA微陣列在單核苷酸多型性的辨別率,我們在DNA微陣列雜交反應後加入了氧化石墨烯。在本論文中我們藉由模擬以及使用合成序列做為檢測樣本證實我們的平台可在短時間(約三小時)完成檢測並成功分辨單核苷酸多型性。接著使用臨床樣本證實此平台與檢測方式可用於臨床分析。我們相信此自動化微流道檢測平台有潛力達成各式基因變異的檢測,以及使基因檢測更加普及化。 | zh_TW |
dc.description.abstract | Upon the completion of the Human Genome Project in 2003, scientists discovered that an astonishing 99% of the 3 billion base pairs in humans are the same in all people. This 1% difference between individuals is known as genetic variation, and can be used to explain the differences between each individual’s disease susceptibility and drug response. Remarkably, up to 90% of all genetic variations are caused by single nucleotide polymorphisms (SNPs), which are point mutations occurring in more than 1% of the population. With several individuals having the same SNP, researchers can specifically identify the relationships between the SNPs and the individual’s disease susceptibility and drug response. Since SNPs are the key enabler of personalized medicine, it is important that we have a quick and effective way to identify SNPs. In this thesis, a fully automatic microfluidic DNA microarray platform for detecting SNPs is developed. To minimize the experiment handling process and shorten the hybridization time, an automatic system applying reciprocating flow is designed. To enhance the signal difference between ssDNA and dsDNA, graphene oxide (GO) is integrated to quench the non-specific fluorescence signals. Our study first demonstrated uniform hybridization conditions with simulations and oligonucleotide sequences. Then, an automatic point-mutation detection of clinical sample is completed by our platform in under 3 hours. We believe this platform can potentially be used to detect all types of genetic variations. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T02:11:25Z (GMT). No. of bitstreams: 1 ntu-106-R04945032-1.pdf: 4994776 bytes, checksum: cbfae4f87523afce794d4e9cbbdc7d3d (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | CONTENTS
口試委員會審定書 # 誌謝 i 中文摘要 iii ABSTRACT iv CONTENTS v LIST OF FIGURES viii LIST OF TABLES x Chapter 1 Introduction 1 1.1 Research Background 1 1.1.1 DNA 1 1.1.2 Genetic Variation 1 1.1.3 Single Nucleotide Polymorphism 3 1.1.4 .Microfluidic DNA Microarray 6 1.2 Literature Review 8 1.2.1 Interaction between Graphene Oxide and DNA 10 1.2.2 Quenching Ability of Graphene Oxide 10 1.2.3 Sensing Mechanism of Graphene Oxide 11 1.2.4 Examples of Graphene Oxide-DNA Based Sensors 12 1.3 Research Motivation 21 1.4 Thesis Structure 21 Chapter 2 Experimental Design 23 2.1 Graphene Oxide and DNA Microarray 24 2.1.1 Probe Design 24 2.1.2 SYBR Green I 24 2.1.3 Graphene Oxide 25 2.1.4 GO-assisted DNA Microarray Protocol 25 2.2 Microfluidic Device 27 2.2.1 PMMA Channel 27 2.2.2 Adhesive Layer 27 2.2.3 Microfluidic Device Fixture 28 2.3 Automatic Microfluidic Platform 29 Chapter 3 Materials and Methods 32 3.1 Microfluidic Microarray Device Fabrication 32 3.1.1 PMMA Microfluidic Channel Fabrication 32 3.1.2 PDMS Layer 33 3.1.3 Microfluidic Device Fixture 33 3.1.4 DNA Microarray Chip Fabrication 34 3.2 DNA Probes and Oligonucleotide Targets 37 3.3 Clinical Sample Preparation 38 3.4 GO-assisted DNA Microarray 41 3.4.1 Graphene Oxide Preparation 41 3.4.2 Reagent Preparation 42 3.4.3 DNA Microarray Hybridization Protocols using the Automatic Microfluidic DNA Microarray Platform 43 3.5 Fluorescent Microscope Imaging 44 3.6 Data Analysis 44 3.7 Simulation Theory in Microfluidic Channel 47 Chapter 4 Results and Discussion 48 4.1 COMSOL Simulation Results 48 4.2 Hybridization Test Under the Reciprocating Flow 50 4.3 Graphene Oxide Size Modification 51 4.4 Graphene Oxide Quenching Efficiency 52 4.5 Multiple Point-Mutation Sequencing Test 56 4.6 Clinical Sample Test 59 Chapter 5 Conclusion 61 Chapter 6 Future Work 62 References 63 | |
dc.language.iso | en | |
dc.title | 使用氧化石墨烯進行單核苷酸多型性檢測之自動化微流道 DNA 微陣列晶片系統 | zh_TW |
dc.title | An Automatic Microfluidic DNA Microarray Platform Utilizing Graphene Oxide for Single Nucleotide Polymorphism Detection | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 莊曜宇,蔡孟勳,盧彥文 | |
dc.subject.keyword | 微流道,自動化,微陣列晶片, | zh_TW |
dc.subject.keyword | Microfluidic,DNA microarray,graphene oxide, | en |
dc.relation.page | 66 | |
dc.identifier.doi | 10.6342/NTU201800064 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-01-15 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
顯示於系所單位: | 生醫電子與資訊學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-106-1.pdf 目前未授權公開取用 | 4.88 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。