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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 周信宏 | |
| dc.contributor.author | Yun-Ju Lee | en |
| dc.contributor.author | 李昀儒 | zh_TW |
| dc.date.accessioned | 2021-06-08T03:55:03Z | - |
| dc.date.copyright | 2018-08-21 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-15 | |
| dc.identifier.citation | 1 Andrianantoandro, E., Basu, S., Karig, D. K., & Weiss, R. (2006). Synthetic biology: new engineering rules for an emerging discipline. Mol Syst Biol, 2, 2006 0028. doi:10.1038/msb4100073
2 Hersch, S. J., Elgamal, S., Katz, A., Ibba, M., & Navarre, W. W. (2014). Translation initiation rate determines the impact of ribosome stalling on bacterial protein synthesis. J Biol Chem, 289(41), 28160-28171. doi:10.1074/jbc.M114.593277 3 Na, D., & Lee, D. (2010). RBSDesigner: software for designing synthetic ribosome binding sites that yields a desired level of protein expression. Bioinformatics, 26(20), 2633-2634. doi:10.1093/bioinformatics/btq458 4 Reeve, B., Hargest, T., Gilbert, C., & Ellis, T. (2014). Predicting translation initiation rates for designing synthetic biology. Front Bioeng Biotechnol, 2, 1. doi:10.3389/fbioe.2014.00001 5 Reis, A. C., & Salis, H. (2017). An automated model test system for systematic development and improvement of gene expression models. doi:10.1101/193367 6 Salis, H. M. (2011). The ribosome binding site calculator. Methods Enzymol, 498, 19-42. doi:10.1016/B978-0-12-385120-8.00002-4 7 Seo, S. W., Yang, J. S., Cho, H. S., Yang, J., Kim, S. C., Park, J. M., Kim, S., Jung, G. Y. (2014). Predictive combinatorial design of mRNA translation initiation regions for systematic optimization of gene expression levels. Sci Rep, 4, 4515. doi:10.1038/srep04515 8 Cheng, Y.-J. (2017). Exploring the sequence space of the Shine-Dalgarno sequence in translation initiation. Unpublished master thesis, National Taiwan University, Taiwan. doi:10.6342/NTU201800124 9 Cohen, S. N., & Chang, A. C. Y. (1977). Revised Interpretation of the Origin of the pSC101 Plasmid. Journal of Bacteriology, 132(2), 734-737. 10 Evfratov, S. A., Osterman, I. A., Komarova, E. S., Pogorelskaya, A. M., Rubtsova, M. P., Zatsepin, T. S., . . . Dontsova, O. A. (2017). Application of sorting and next generation sequencing to study 5-UTR influence on translation efficiency in Escherichia coli. Nucleic Acids Res, 45(6), 3487-3502. doi:10.1093/nar/gkw1141 11 Illumina (2013). 16S Metagenomic Sequencing Library Preparation. https://www.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep-guide-15044223-b.pdf 12 Kosuri, S., Goodman, D. B., Cambray, G., Mutalik, V. K., Gao, Y., Arkin, A. P., Church, G. M. (2013). Composability of regulatory sequences controlling transcription and translation in Escherichia coli. Proc Natl Acad Sci U S A, 110(34), 14024-14029. doi:10.1073/pnas.1301301110 Peterman, N., & Levine, E. (2016). Sort-seq under the hood: implications of design choices on large-scale characterization of sequence-function relations. BMC Genomics, 17, 206. doi:10.1186/s12864-016-2533-5 13 Rohlhill, J., Sandoval, N. R., & Papoutsakis, E. T. (2017). Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol. ACS Synthetic Biology, 6(8), 1584-1595. doi:10.1021/acssynbio.7b00114 14 Salis, H. M., Mirsky, E. A., & Voigt, C. A. (2009). Automated design of synthetic ribosome binding sites to control protein expression. Nat Biotechnol, 27(10), 946-950. doi:10.1038/nbt.1568 15 van Rossum, G., Python tutorial, Technical Report CS-R9526, Centrum voor Wiskunde en Informatica (CWI), Amsterdam, May 1995. 16 Espah Borujeni, A., Channarasappa, A. S., & Salis, H. M. (2014). Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites. Nucleic Acids Res, 42(4), 2646-2659. doi:10.1093/nar/gkt1139 17 Gruber, A. R., Lorenz, R., Bernhart, S. H., Neubock, R., & Hofacker, I. L. (2008). The Vienna RNA websuite. Nucleic Acids Res, 36(Web Server issue), W70-74. doi:10.1093/nar/gkn188 18 Osterman, I. A., Evfratov, S. A., Sergiev, P. V., & Dontsova, O. A. (2013). Comparison of mRNA features affecting translation initiation and reinitiation. Nucleic Acids Res, 41(1), 474-486. doi:10.1093/nar/gks989 19 Deneke, C., Lipowsky, R., & Valleriani, A. (2013). Effect of ribosome shielding on mRNA stability. Phys Biol, 10(4), 046008. doi:10.1088/1478-3975/10/4/046008 20 Livak, K. J., & Schmittgen, T. D. (2001). Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods, 25(4), 402-408. doi:10.1006/meth.2001.1262 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21958 | - |
| dc.description.abstract | 合成生物學致力於組裝來自於不同生物體的元件以建造嶄新的基因或代謝途徑。要達成這樣的目的,準確調控連接各個迴路部分的蛋白質表現量非常關鍵。先前的研究已建立根據編碼區上游的信使核醣核酸的序列來預測蛋白質的轉譯速率的熱力學模型,雖然這些模型有考慮到信使核醣核酸的折疊能量,卻忽略其確切的結構型態對轉譯的影響。為了解信使核糖核酸二級結構對轉譯的影響,我做出綠色螢光蛋白的Shine-Dalgarno序列周邊9個核苷酸的所有排列可能的質體。將這些質體送進大腸桿菌之後,我用流式細胞術和次世代定序去量化各個序列種類的轉譯速率。我的結果顯示之前宣稱具有準確預測能力的熱力學模型實際上預測很差。具有髮夾結構將Shine-Dalgarno序列遮蔽的信使核糖核酸能顯著抑制轉譯。帶有一致周邊序列但不同的Shine-Dalgarno序列所造成的二級結構效應也不相同。藉由釐清被現有模型忽視的要素,我的研究可增進我們對細菌轉譯的根本認知、改善計算預測的準確性並加速達到合成生物學的目標。 | zh_TW |
| dc.description.abstract | Synthetic biology aims for building novel genetic or metabolic pathways by assembling elements from different organisms. To this end, precise control of the protein expression levels connecting each part of the circuit is crucial. Prior works have established thermodynamics models that predict translation rate of a protein based on the mRNA sequence upstream of the coding region. Although these models consider the mRNA folding energy, they neglect the influence of exact mRNA conformation on ribosome binding. To identify the influence of mRNA secondary structure on translation, I applied saturated mutagenesis to the 9 nucleotides flanking the Shine-Dalgarno (SD) sequence of a green fluorescent protein (GFP) gene on the plasmids. Upon transformation into Escherichia coli, I used fluorescence-activated cell sorting and next-generation sequencing to profile the translation rate of each sequence variant. My results show that the thermodynamic model, formerly claimed to be accurate, actually makes poor prediction. Particularly, mRNA hairpins which sequester the SD sequence inhibit translation significantly. The flanking sequences also have different effects on different SD sequence background. By identifying factors ignored by the current model, my study may advance our fundamental understanding of protein translation in bacteria, improve the accuracy of computational prediction, and facilitate the goal of synthetic biology. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T03:55:03Z (GMT). No. of bitstreams: 1 ntu-107-R05b21016-1.pdf: 5458590 bytes, checksum: 84e124143f7e7f139ad0bf6edf3dbdd1 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 口試委員審定書 I
謝誌 II 摘要 III Abstract IV Contents VI Figures VIII Tables X Chapter I. Introduction 1 Reference 2 Chapter II. High-throughput measurement 4 2-1 Standby site and spacer randomized (SSR) library construction 5 2-2 Cell sorting 9 2-3 NGS data arrangement 15 2-4 Correlation of replicate experiments 16 2-5 Discussion 18 2-6 Materials and methods 20 Reference 29 Chapter III. Analyses of structural influences on translation initiation 32 3-1 Library distribution of translation efficiency 32 3-2 Correlation between the experiments and the model prediction 33 3-3 Steady hairpin inhibits translation 36 3-4 Influence of standby site and spacer motifs 39 3-5 Comparison of pYC08-SSR and pYL17-SSR library 42 3-6 Discussion 44 3-7 Materials and methods 45 References 48 Chapter IV. Transcriptional influences 50 4-1 Influence of protein translation on mRNA levels 50 4-2 Discussion 51 4-3 Materials and methods 52 References 56 Chapter Ⅴ. Conclusion 57 | |
| dc.language.iso | en | |
| dc.title | 高通量分析信使核糖核酸的二級結構對轉譯起始的影響 | zh_TW |
| dc.title | High-throughput Analysis of the Effect of mRNA
Secondary Structure on Translation Initiation | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 溫進德,鄭貽生,葉怡均 | |
| dc.subject.keyword | 合成生物學,轉譯起始,核醣體結合位點,流式定序,信使核糖核酸二級結構, | zh_TW |
| dc.subject.keyword | Synthetic biology,translation initiation,ribosome binding site,Flowseq,mRNA secondary structure, | en |
| dc.relation.page | 58 | |
| dc.identifier.doi | 10.6342/NTU201803699 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2018-08-16 | |
| dc.contributor.author-college | 生命科學院 | zh_TW |
| dc.contributor.author-dept | 生命科學系 | zh_TW |
| 顯示於系所單位: | 生命科學系 | |
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