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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃念祖(Nien-Tsu Huang) | |
| dc.contributor.author | Yu-Shin Chang | en |
| dc.contributor.author | 張郁欣 | zh_TW |
| dc.date.accessioned | 2021-06-16T09:49:59Z | - |
| dc.date.available | 2019-02-16 | |
| dc.date.copyright | 2017-02-16 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2017-01-19 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60003 | - |
| dc.description.abstract | 本研究論文開發一自動化微流道DNA微陣列檢測平台，用於長Q-T症候群(Long QT syndrome，以下簡稱LQTS)之單核苷酸多型性檢測。LQTS是一種先天性的心臟疾病，可能會引發致死性的心律不整。目前科學家發現數個基因的突變和LQTS有關，已知有超過700個點突變位點會造成不同類型的LQTS。目前臨床利用DNA微陣列檢測基因型，診斷病人患有的LQTS類型並給予適當的治療。然而傳統的DNA微陣列檢測除了成本昂貴(一個樣本1500-3000美元)之外，基因檢測需要4至6週才能得到檢驗報告，十分耗時。為了解決檢測時間過長的問題，我們設計微流道DNA微陣列晶片，縮小樣本的反應體積使得表面積/體積比增加，縮短反應時間。並利用微幫浦進行主動混合，增加樣本DNA和探針DNA接觸雜交的機會。另外由於DNA微陣列需要繁雜的操作步驟，因此我們將微流道DNA微陣列晶片和商業化的微流道系統為基底(包含微幫浦、微閥門、閥門控制器及液體收集區)整合，設計出自動化的檢測平台。自動化微流道DNA微陣列檢測平台可以利用程式控制流體流入微流道的流速和體積，使樣本在微流道中和下方DNA微陣列上的DNA 探針做雜交反應 (Hybridization)。為了提升檢測單核苷酸多型性的專一性，我們在正常 (Wild type) 和突變 (Mutant) 兩種探針加入額外的點突變，以增加兩者雜交反應的差異性。最後再加入SYBR green I 螢光染劑標定雙股DNA。本論文首先將雜交的條件最佳化，包括雜交的反應溫度和流體速度，以及SYBR green I的染色條件。接著利用寡核甘酸exon12 WT 和exon12 MU做為目標序列，證實透過我們所研發的自動化微流道DNA微陣列檢測平台可以區分單核苷酸多型性。接著再以病人檢體做檢測。相較於目前的DNA微陣列，自動化微流道DNA微陣列檢測平台可以自動化的完成雜交複雜的實驗流程，不但節省反應時間也同時降低人工成本及可能的人為誤差。 此外利用SYBR green I 做為螢光染劑可省去樣本前處理的標定動作，使的操作起來更方便迅速。此自動化微流道DNA微陣列檢測平台有潛力達到高通量、快速、反應靈敏的單核苷酸多型性檢測。 | zh_TW |
| dc.description.abstract | In this thesis, we have developed an automatic microfluidic DNA microarray system for single nucleotide polymorphism (SNP) screening for Long QT syndrome (LQTS). LQTS is a genetic heart disease caused by SNPs and genetic screening is the most effective diagnosis method. DNA microarray is one of the most powerful methods which can screen thousands of genes on a single chip. However, conventional DNA microarray is time-consuming (at least 16 hours) since the target and probe DNA hybridization is based on the passive diffusion. To address this problem, we integrated a microfluidic system with DNA microarray to reduce the hybridization time from 16 to 2 hours by active mixing and minimizing the manual operation process. Our study first optimized the hybridization conditions, including hybridization temperature and sample flow rate. Then, to differentiate the SNPs between wild type and mutation probes, we placed an additional mismatch on both types of probes. The results showed that the SNPs could be effectively detected (or differentiated). Compared to current DNA microarray methods, automatic microfluidic DNA microarray can minimize the manual manipulation. Besides, by reducing the assay reagent volume and using the active mixing in the hybridization process, the total assay time can be reduced to 3 hours, which is eight times shorter than conventional DNA microarray. With the higher selectivity of SNPs, short hybridization time, and automatic procedure, we believe that our device has the potential to achieve high-throughput, rapid and sensitive gene screening test. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T09:49:59Z (GMT). No. of bitstreams: 1 ntu-105-R03945020-1.pdf: 4192741 bytes, checksum: 54c3bf27155b88d96643f522f436c72e (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 iii ABSTRACT iv CONTENTS v FIGURE CONTENTS viii TABLE CONTENTS x Chapter 1 Introduction 11 1.1 Background 11 1.2 Research motivation 14 1.2.1 Long QT Syndrome 14 1.2.2 DNA microarray for SNP genotyping 16 1.2.3 Microfluidic-based DNA microarray 17 1.3 Literature review 18 1.4 Thesis structure 25 Chapter 2 Experimental design 26 2.1 Microfluidic chip design 26 2.2 Automatic microfluidic system 27 2.3 DNA microarray assay 29 2.3.1 Probe design 29 2.3.2 SYBR green I fluorescent dye 30 2.3.3 DNA microarray assays workflow 30 Chapter 3 Materials and Methods 32 3.1 PMMA microfluidic chip fabrication 32 3.2 COMSOL simulation of flow in the microfluidic chip 32 3.3 DNA microarray spotting 33 3.4 DNA probes and oligonucleotide targets 36 3.5 PCR protocol 37 3.6 Microfluidic DNA microarray hybridization 38 3.7 Conventional DNA microarray hybridization 42 3.8 Fluorescent image and data analysis 42 Chapter 4 Results and discussion 43 4.1 Simulation results 43 4.2 Stability test 46 4.3 Microfluidic DNA hybridization condition optimization 47 4.3.1 Hybridization temperature optimization 47 4.3.2 Hybridization flow rate optimization 49 4.4 Hybridization results with Cy3 labeled DNA target 50 4.4.1 Different exon analysis 50 4.4.2 SNP analysis 50 4.5 SYBR green I condition optimization 53 4.5.1 SYBR green I concentration optimization 53 4.5.2 Washing condition optimization 54 4.6 Hybridization results with SYBR green I 56 4.6.1 Different exons analysis 56 4.6.2 SNP analysis 56 4.7 Comparison of microfluidic and conventional microarray 60 4.7.1 PCR of clinical sample 60 4.7.2 SNP analysis of clinical sample 60 4.8 The enhancement of background uniformity by Graphene Oxide 64 Chapter 5 Conclusion 66 Chapter 6 Future work 68 Reference 69 | |
| dc.language.iso | en | |
| dc.subject | 微流道 | zh_TW |
| dc.subject | DNA 微陣列 | zh_TW |
| dc.subject | 自動化 | zh_TW |
| dc.subject | 長QT症候群 | zh_TW |
| dc.subject | 單核?酸多型性 | zh_TW |
| dc.subject | microfluidics | en |
| dc.subject | DNA microarray | en |
| dc.subject | automatic | en |
| dc.subject | Long QT Syndrome | en |
| dc.subject | single nucleotide polymorphism | en |
| dc.title | 開發自動化微流道DNA微陣列晶片應用於長Q-T症候群之單核苷酸多型性檢測 | zh_TW |
| dc.title | An Automatic Microfluidic DNA Microarray Platform for Single Nucleotide Polymorphism Screening of Long QT Syndrome | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 莊曜宇(Eric Y. Chuang),蔡孟勳(Mong-Hsun Tsai),盧彥文(Yen-Wen Lu) | |
| dc.subject.keyword | 微流道,DNA 微陣列,自動化,長QT症候群,單核?酸多型性, | zh_TW |
| dc.subject.keyword | microfluidics,DNA microarray,automatic,Long QT Syndrome,single nucleotide polymorphism, | en |
| dc.relation.page | 72 | |
| dc.identifier.doi | 10.6342/NTU201700129 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-01-19 | |
| 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 | |
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