請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92418完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 周信宏 | zh_TW |
| dc.contributor.advisor | Hsin-Hung Chou | en |
| dc.contributor.author | 郭學庭 | zh_TW |
| dc.contributor.author | Syue-Ting Kuo | en |
| dc.date.accessioned | 2024-03-22T16:24:58Z | - |
| dc.date.available | 2024-03-23 | - |
| dc.date.copyright | 2024-03-22 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-12-05 | - |
| dc.identifier.citation | Chapter 1.
1. Khorana, H. G. et al. CIII. Total synthesis of the structural gene for an alanine transfer ribonucleic acid from yeast. J. Mol. Biol. 72, 209–217 (1972). 2. He, M.-Y. et al. Sensitive and specific cadmium biosensor developed by reconfiguring metal transport and leveraging natural gene repositories. ACS Sens. 6, 995–1002 (2021). 3. Atsumi, S., Hanai, T. & Liao, J. C. Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels. Nature 451, 86–89 (2008). 4. Anderson, J. C., Clarke, E. J., Arkin, A. P. & Voigt, C. A. Environmentally controlled invasion of cancer cells by engineered bacteria. J. Mol. Biol. 355, 619–627 (2006). 5. Cox, R. S., Surette, M. G. & Elowitz, M. B. Programming gene expression with combinatorial promoters. Mol. Syst. Biol. 3, 145 (2007). 6. Carr, P. A. & Church, G. M. Genome engineering. Nat. Biotechnol. 27, 1151–1162 (2009). 7. Temme, K., Zhao, D. & Voigt, C. A. Refactoring the nitrogen fixation gene cluster from Klebsiella oxytoca. Proc. Natl. Acad. Sci. 109, 7085–7090 (2012). 8. Bonnet, J., Subsoontorn, P. & Endy, D. Rewritable digital data storage in live cells via engineered control of recombination directionality. Proc. Natl. Acad. Sci. 109, 8884–8889 (2012). 9. Ro, D.-K. et al. Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Nature 440, 940–943 (2006). 10. Steen, E. J. et al. Microbial production of fatty-acid-derived fuels and chemicals from plant biomass. Nature 463, 559–562 (2010). 11. Bervoets, I. & Charlier, D. Diversity, versatility and complexity of bacterial gene regulation mechanisms: opportunities and drawbacks for applications in synthetic biology. FEMS Microbiol. Rev. 43, 304–339 (2019). 12. Chen, J. et al. Stepwise promoter melting by bacterial RNA polymerase. Mol. Cell 78, 275-288. e6 (2020). 13. Paget, M. S. & Helmann, J. D. The σ70 family of sigma factors. Genome Biol. 4, 203 (2003). 14. Tierrafría, V. H. et al. RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12. Microb. Genomics 8, 000833 (2022). 15. Feklístov, A., Sharon, B. D., Darst, S. A. & Gross, C. A. Bacterial sigma factors: a historical, structural, and genomic perspective. Annu. Rev. Microbiol. 68, 357–376 (2014). 16. Zuo, Y. & Steitz, T. A. Crystal structures of the E. coli transcription initiation complexes with a complete bubble. Mol. Cell 58, 534–540 (2015). 17. Blatter, E. E., Ross, W. & Gourse, R. L. Domain organization of RNA polymerase α subunit: C-terminal 85 amino acids constitute a domain capable of dimerization and DNA binding. (1994). 18. Ross, W. et al. A third recognition element in bacterial promoters: DNA binding by the α subunit of RNA polymerase. Sci. New Ser. 262, 1407–1413 (1993). 19. Hawley, D. K. & McClure, W. R. Compilation and analysis of Escherichia coli promoter DNA sequences. Nucleic Acids Res. 11, 2237–2255 (1983). 20. Siebenlist, U., Simpson, R. B. & Gilbert, W. E. coli RNA polymerase interacts homologously with two different promoters. Cell 20, 269–281 (1980). 21. Rosenberg, M. & Court, D. Regulatory sequences involved in the promotion and termination of RNA transcription. Annu. Rev. Genet. 13, 319–353 (1979). 22. Van Hijum, S. A. F. T., Medema, M. H. & Kuipers, O. P. Mechanisms and evolution of control logic in prokaryotic transcriptional regulation. Microbiol. Mol. Biol. Rev. 73, 481–509 (2009). 23. Browning, D. F. & Busby, S. J. W. The regulation of bacterial transcription initiation. Nat. Rev. Microbiol. 2, 57–65 (2004). 24. Browning, D. F. & Busby, S. J. W. Local and global regulation of transcription initiation in bacteria. Nat. Rev. Microbiol. 14, 638–650 (2016). 25. Wen, J.-D., Kuo, S.-T. & Chou, H.-H. D. The diversity of Shine-Dalgarno sequences sheds light on the evolution of translation initiation. RNA Biol. 18, 1489–1500 (2021). 26. Laursen, B. S., Sørensen, H. P., Mortensen, K. K. & Sperling-Petersen, H. U. Initiation of protein synthesis in bacteria. Microbiol. Mol. Biol. Rev. 69, 101–123 (2005). 27. Nakamoto, T. Evolution and the universality of the mechanism of initiation of protein synthesis. Gene 432, 1–6 (2009). 28. Shine, J. & Dalgarno, L. Determinant of cistron specificity in bacterial ribosomes. Nature 254, 34–38 (1975). 29. Davis, J. H., Rubin, A. J. & Sauer, R. T. Design, construction and characterization of a set of insulated bacterial promoters. Nucleic Acids Res. 39, 1131–1141 (2011). 30. Barrick, D. et al. Quantitative analysis of ribosome binding sites in E.coli. Nucleic Acids Res. 22, 1287–1295 (1994). 31. Ross, W., Aiyar, S. E., Salomon, J. & Gourse, R. L. Escherichia coli promoters with UP elements of different strengths: modular structure of bacterial promoters. J. Bacteriol. 180, 5375–5383 (1998). 32. Valgepea, K., Adamberg, K., Seiman, A. & Vilu, R. Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins. Mol. Biosyst. 9, 2344–2358 (2013). 33. Campo, C. D., Bartholomäus, A., Fedyunin, I. & Ignatova, Z. Secondary structure across the bacterial transcriptome reveals versatile roles in mRNA regulation and function. PLOS Genet. 11, e1005613 (2015). 34. Balakrishnan, R. et al. Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria. Science 378, eabk2066 (2022). 35. Gottesman, S. Micros for microbes: non-coding regulatory RNAs in bacteria. Trends Genet. 21, 399–404 (2005). 36. Patwardhan, R. P. et al. High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis. Nat. Biotechnol. 27, 1173–1175 (2009). 37. Scholz, S. A., Lindeboom, C. D. & Freddolino, P. L. Genetic context effects can override canonical cis regulatory elements in Escherichia coli. Nucleic Acids Res. 50, 10360–10375 (2022). 38. Kudla, G., Murray, A. W., Tollervey, D. & Plotkin, J. B. Coding-sequence determinants of gene expression in Escherichia coli. Science 324, 255–258 (2009). 39. Boël, G. et al. Codon influence on protein expression in E. coli correlates with mRNA levels. Nature 529, 358–363 (2016). 40. Kinney, J. B. & McCandlish, D. M. Massively parallel assays and quantitative sequence–function relationships. Annu. Rev. Genomics Hum. Genet. 20, 99–127 (2019). 41. Kinney, J. B., Murugan, A., Callan, C. G. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl. Acad. Sci. 107, 9158–9163 (2010). 42. de Boer, C. G. et al. Deciphering eukaryotic gene-regulatory logic with 100 million random promoters. Nat. Biotechnol. 38, 56–65 (2020). 43. Arnold, C. D. et al. Genome-wide quantitative enhancer activity maps identified by STARR-seq. Science 339, 1074–1077 (2013). 44. Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30, 271–277 (2012). 45. Kwasnieski, J. C., Mogno, I., Myers, C. A., Corbo, J. C. & Cohen, B. A. Complex effects of nucleotide variants in a mammalian cis-regulatory element. Proc. Natl. Acad. Sci. 109, 19498–19503 (2012). 46. Patwardhan, R. P. et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30, 265–270 (2012). 47. Urtecho, G., Tripp, A. D., Insigne, K. D., Kim, H. & Kosuri, S. Systematic dissection of sequence elements controlling σ70 promoters using a genomically encoded multiplexed reporter assay in Escherichia coli. Biochemistry 58, 1539–1551 (2018). 48. Dvir, S. et al. Deciphering the rules by which 5′-UTR sequences affect protein expression in yeast. Proc. Natl. Acad. Sci. 110, E2792–E2801 (2013). 49. Oikonomou, P., Goodarzi, H. & Tavazoie, S. Systematic identification of regulatory elements in conserved 3′ UTRs of human transcripts. Cell Rep. 7, 281–292 (2014). 50. Baeza-Centurion, P., Miñana, B., Schmiedel, J. M., Valcárcel, J. & Lehner, B. Combinatorial genetics reveals a scaling law for the effects of mutations on splicing. Cell 176, 549-563. e23 (2019). 51. Cambray, G., Guimaraes, J. C. & Arkin, A. P. Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli. Nat. Biotechnol. 36, 1005–1015 (2018). 52. LaFleur, T. L., Hossain, A. & Salis, H. M. Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. Nat. Commun. 13, 5159 (2022). 53. Rohlhill, J., Sandoval, N. R. & Papoutsakis, E. T. Sort-seq approach to engineering a formaldehyde-inducible promoter for dynamically regulated Escherichia coli growth on methanol. ACS Synth. Biol. 6, 1584–1595 (2017). 54. Ireland, W. T. et al. Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time. eLife 9, e55308 (2020). 55. Kosuri, S. et al. Composability of regulatory sequences controlling transcription and translation in Escherichia coli. Proc. Natl. Acad. Sci. 110, 14024–14029 (2013). 56. Zhou, J. et al. Higher-order epistasis and phenotypic prediction. Proc. Natl. Acad. Sci. 119, e2204233119 (2022). 57. Van Brempt, M. et al. Predictive design of sigma factor-specific promoters. Nat. Commun. 11, 5822 (2020). 58. Bintu, L. et al. Transcriptional regulation by the numbers: models. Curr. Opin. Genet. Dev. 15, 116–124 (2005). 59. Yuan-Ju, C. Exploring the sequence space of the Shine-Dalgarno sequence in translation initiation. (National Taiwan University, 2017). 60. Wei-Yi, S. Functional dissection of E. coli σ70 promoters at single-nucleotide resolution. (National Taiwan University, 2022). Chapter 2. Aguilar-Rodriguez J, Payne JL, Wagner A. 2017. A thousand empirical adaptive landscapes and their navigability. Nat Ecol Evol 1: 45. Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H. 2006. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol 2: 2006.0008. Blanco C, Janzen E, Pressman A, Saha R, Chen IA. 2019. Molecular fitness landscapes from high-coverage sequence profiling. Annu Rev Biophys 48: 1-18. Bonde MT, Pedersen M, Klausen MS, Jensen SI, Wulff T, Harrison S, Nielsen AT, Herrgard MJ, Sommer MOA. 2016. Predictable tuning of protein expression in bacteria. Nat Methods 13: 233-236. Boni IV, Isaeva DM, Musychenko ML, Tzareva NV. 1991. Ribosome-messenger recognition: mRNA target sites for ribosomal protein S1. Nucleic Acids Res 19: 155-162. Chang B, Halgamuge S, Tang SL. 2006. Analysis of SD sequences in completed microbial genomes: non-SD-led genes are as common as SD-led genes. Gene 373: 90-99. Chen H, Bjerknes M, Kumar R, Jay E. 1994. Determination of the optimal aligned spacing between the Shine-Dalgarno sequence and the translation initiation codon of Escherichia coli mRNAs. Nucleic Acids Res 22: 4953-4957. Chou HH, Chiu HC, Delaney NF, Segre D, Marx CJ. 2011. Diminishing returns epistasis among beneficial mutations decelerates adaptation. Science 332: 1190-1192. Chou HH, Marx CJ, Sauer U. 2015. Transhydrogenase promotes the robustness and evolvability of E. coli deficient in NADPH production. PLoS Genet 11: e1005007. Cormack BP, Valdivia RH, Falkow S. 1996. FACS-optimized mutants of the green fluorescent protein (GFP). Gene 173: 33-38. Datsenko KA, Wanner BL. 2000. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc Natl Acad Sci USA 97: 6640-6645. Davis JH, Rubin AJ, Sauer RT. 2011. Design, construction and characterization of a set of insulated bacterial promoters. Nucleic Acids Res 39: 1131-1141. de Smit MH, van Duin J. 1990. Secondary structure of the ribosome binding site determines translational efficiency: a quantitative analysis. Proc Natl Acad Sci USA 87: 7668-7672. Domingo J, Baeza-Centurion P, Lehner B. 2019. The causes and consequences of genetic interactions (epistasis). Annu Rev Genomics Hum Genet 20: 17.11-17.28. Domingo J, Diss G, Lehner B. 2018. Pairwise and higher-order genetic interactions during the evolution of a tRNA. Nature 558: 117-121. Duval M, Korepanov A, Fuchsbauer O, Fechter P, Haller A, Fabbretti A, Choulier L, Micura R, Klaholz BP, Romby P et al. 2013. Escherichia coli ribosomal protein S1 unfolds structured mRNAs onto the ribosome for active translation initiation. PLoS Biol 11: e1001731. Espah Borujeni A, Channarasappa AS, Salis HM. 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: 2646-2659. Eyre-Walker A, Keightley PD. 2007. The distribution of fitness effects of new mutations. Nat Rev Genet 8: 610-618. Gao R, Yu K, Nie JK, Lian TF, Jin JS, Liljas A, Su XD. 2016. Deep sequencing reveals global patterns of mRNA recruitment during translation initiation. Sci Rep 6: 30170. Gorochowski TE, Chelysheva I, Eriksen M, Nair P, Pedersen S, Ignatova Z. 2019. Absolute quantification of translational regulation and burden using combined sequencing approaches. Mol Syst Biol 15: e8719. Gupta RD, Tawfik DS. 2008. Directed enzyme evolution via small and effective neutral drift libraries. Nat Methods 5: 939-942. Harms MJ, Thornton JW. 2014. Historical contingency and its biophysical basis in glucocorticoid receptor evolution. Nature 512: 203-207. Hayashi K, Morooka N, Yamamoto Y, Fujita K, Isono K, Choi S, Ohtsubo E, Baba T, Wanner BL, Mori H et al. 2006. Highly accurate genome sequences of Escherichia coli K-12 strains MG1655 and W3110. Mol Syst Biol 2: 2006 0007. Hayden EJ, Ferrada E, Wagner A. 2011. Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature 474: 92-95. Hockenberry AJ, Stern AJ, Amaral LAN, Jewett MC. 2018. Diversity of translation initiation mechanisms across bacterial species is driven by environmental conditions and growth demands. Mol Biol Evol 35: 582–592. Kosuri S, Goodman DB, Cambray G, Mutalik VK, Gao Y, Arkin AP, Endy D, Church GM. 2013. Composability of regulatory sequences controlling transcription and translation in Escherichia coli. Proc Natl Acad Sci USA 110: 14024-14029. Kurylo CM, Alexander N, Dass RA, Parks MM, Altman RA, Vincent CT, Mason CE, Blanchard SC. 2016. Genome sequence and analysis of Escherichia coli MRE600, a colicinogenic, nonmotile strain that lacks RNase I and the Type I methyltransferase, EcoKI. Genome Biol Evol 8: 742-752. Laursen BS, Sorensen HP, Mortensen KK, Sperling-Petersen HU. 2005. Initiation of protein synthesis in bacteria. Microbiol Mol Biol Rev 69: 101-123. Li C, Qian WF, Maclean CJ, Zhang JZ. 2016. The fitness landscape of a tRNA gene. Science 352: 837-840. Lorenz R, Bernhart SH, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL. 2011. ViennaRNA Package 2.0. Algorithms Mol Biol 6: 26. Maynard Smith J. 1970. Natural selection and concept of a protein space. Nature 225: 563-564. Nagai T, Ibata K, Park ES, Kubota M, Mikoshiba K, Miyawaki A. 2002. A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat Biotechnol 20: 87-90. Nakagawa S, Niimura Y, Miura K, Gojobori T. 2010. Dynamic evolution of translation initiation mechanisms in prokaryotes. Proc Natl Acad Sci USA 107: 6382-6387. Omotajo D, Tate T, Cho H, Choudhary M. 2015. Distribution and diversity of ribosome binding sites in prokaryotic genomes. BMC Genomics 16: 604. Orr HA. 2005. The genetic theory of adaptation: a brief history. Nat Rev Genet 6: 119-127. Osterman IA, Evfratov SA, Sergiev PV, Dontsova OA. 2013. Comparison of mRNA features affecting translation initiation and reinitiation. Nucleic Acids Res 41: 474-486. Payne JL, Wagner A. 2014. The robustness and evolvability of transcription factor binding sites. Science 343: 875-877. Podgornaia AI, Laub MT. 2015. Pervasive degeneracy and epistasis in a protein-protein interface. Science 347: 673-677. R Core Team. 2019. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Rodnina MV. 2016. The ribosome in action: Tuning of translational efficiency and protein folding. Protein Sci 25: 1390-1406. Salis HM, Mirsky EA, Voigt CA. 2009. Automated design of synthetic ribosome binding sites to control protein expression. Nat Biotechnol 27: 946-950. Sanner MF. 1999. Python: A programming language for software integration and development. J Mol Graph Model 17: 57-61. Sarkisyan KS, Bolotin DA, Meer MV, Usmanova DR, Mishin AS, Sharonov GV, Ivankov DN, Bozhanova NG, Baranov MS, Soylemez O et al. 2016. Local fitness landscape of the green fluorescent protein. Nature 533: 397-401. Scharff LB, Childs L, Walther D, Bock R. 2011. Local absence of secondary structure permits translation of mRNAs that lack ribosome-binding sites. PLoS Genet 7: e1002155. Shine J, Dalgarno L. 1975. Determinant of cistron specificity in bacterial ribosomes. Nature 254: 34-38. Tokuriki N, Jackson CJ, Afriat-Jurnou L, Wyganowski KT, Tang R, Tawfik DS. 2012. Diminishing returns and tradeoffs constrain the laboratory optimization of an enzyme. Nat Commun 3: 1257. Tokuriki N, Tawfik DS. 2009. Stability effects of mutations and protein evolvability. Curr Opin Struct Biol 19: 596-604. Varani G, McClain WH. 2000. The G·U wobble base pair. EMBO Rep 1: 18-23. Wagner A. 2008. Robustness and evolvability: a paradox resolved. Proc Biol Sci 275: 91-100. Weinreich DM, Delaney NF, Depristo MA, Hartl DL. 2006. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312: 111-114. Zhang J, Deutscher MP. 1992. A uridine-rich sequence required for translation of prokaryotic mRNA. Proc Natl Acad Sci USA 89: 2605-2609. Chapter 3. 1. Browning, D. F. & Busby, S. J. W. Local and global regulation of transcription initiation in bacteria. Nat Rev Microbiol 14, 638–650 (2016). 2. Chen, J. et al. Stepwise promoter melting by bacterial RNA polymerase. Molecular cell 78, 275-288. e6 (2020). 3. Bervoets, I. & Charlier, D. Diversity, versatility and complexity of bacterial gene regulation mechanisms: opportunities and drawbacks for applications in synthetic biology. FEMS Microbiology Reviews 43, 304–339 (2019). 4. Paget, M. S. & Helmann, J. D. The σ70 family of sigma factors. Genome Biology 4, 203 (2003). 5. Tierrafría, V. H. et al. RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12. Microbial Genomics 8, 000833 (2022). 6. Feklistov, A. & Darst, S. A. Structural basis for promoter -10 element recognition by the bacterial RNA polymerase σ subunit. Cell 147, 1257–1269 (2011). 7. Zhang, Y. et al. Structural basis of transcription initiation. Science 338, 1076–1080 (2012). 8. Feklístov, A., Sharon, B. D., Darst, S. A. & Gross, C. A. Bacterial sigma factors: a historical, structural, and genomic perspective. Annu. Rev. Microbiol. 68, 357–376 (2014). 9. Zuo, Y. & Steitz, T. A. Crystal structures of the E. coli transcription initiation complexes with a complete bubble. Molecular Cell 58, 534–540 (2015). 10. Blatter, E. E., Ross, W. & Gourse, R. L. Domain organization of RNA polymerase α subunit: C-terminal 85 amino acids constitute a domain capable of dimerization and DNA binding. (1994). 11. Ross, W. et al. A third recognition element in bacterial promoters: DNA binding by the α subunit of RNA polymerase. Science, New Series 262, 1407–1413 (1993). 12. Hawley, D. K. & McClure, W. R. Compilation and analysis of Escherichia coli promoter DNA sequences. Nucl Acids Res 11, 2237–2255 (1983). 13. Siebenlist, U., Simpson, R. B. & Gilbert, W. E. coli RNA polymerase interacts homologously with two different promoters. Cell 20, 269–281 (1980). 14. Rosenberg, M. & Court, D. Regulatory sequences involved in the promotion and termination of RNA transcription. Annu. Rev. Genet. 13, 319–353 (1979). 15. Huerta, A. M., Francino, M. P., Morett, E. & Collado-Vides, J. Selection for unequal densities of σ70 promoter-like signals in different regions of large bacterial genomes. PLOS Genetics 2, e185 (2006). 16. Shao, W., Price, M. N., Deutschbauer, A. M., Romine, M. F. & Arkin, A. P. Conservation of transcription start sites within genes across a bacterial genus. mBio 5, e01398-14 (2014). 17. Korostelev, Y. D., Zharov, I. A., Mironov, A. A., Rakhmaininova, A. B. & Gelfand, M. S. Identification of position-specific correlations between DNA-Binding domains and their binding sites. application to the merr family of transcription factors. PLOS ONE 11, e0162681 (2016). 18. Lee, D. J., Minchin, S. D. & Busby, S. J. W. Activating transcription in bacteria. Annual Review of Microbiology 66, 125–152 (2012). 19. Brown, N. L., Stoyanov, J. V., Kidd, S. P. & Hobman, J. L. The MerR family of transcriptional regulators. FEMS Microbiol Rev 27, 145–163 (2003). 20. Cuthbertson, L. & Nodwell, J. R. The TetR family of regulators. Microbiol Mol Biol Rev 77, 440–475 (2013). 21. Swint-Kruse, L. & Matthews, K. S. Allostery in the LacI/GalR family: variations on a theme. Current Opinion in Microbiology 12, 129–137 (2009). 22. Eisen, H., Brachet, P., Silva, L. P. D. & Jacob, F. Regulation of repressor expression in λ. Proc. Natl. Acad. Sci. U.S.A. 66, 855–862 (1970). 23. Rodionov, D. A. Comparative genomic reconstruction of transcriptional regulatory betworks in bacteria. Chem. Rev. 107, 3467–3497 (2007). 24. Cox, R. S., Surette, M. G. & Elowitz, M. B. Programming gene expression with combinatorial promoters. Mol Syst Biol 3, 145 (2007). 25. Bertram, R. & Hillen, W. The application of Tet repressor in prokaryotic gene regulation and expression. Microbial Biotechnology 1, 2–16 (2008). 26. Barnes, S. L., Belliveau, N. M., Ireland, W. T., Kinney, J. B. & Phillips, R. Mapping DNA sequence to transcription factor binding energy in vivo. PLOS Computational Biology 15, e1006226 (2019). 27. Yu, T. C. et al. Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems. Nat Commun 12, 325 (2021). 28. Lawson, C. L. et al. Catabolite activator protein: DNA binding and transcription activation. Current Opinion in Structural Biology 14, 10–20 (2004). 29. Antunes, L. C. M., Ferreira, R. B. R., Lostroh, C. P. & Greenberg, E. P. A mutational analysis defines Vibrio fischeri LuxR binding sites. J Bacteriol 190, 4392–4397 (2008). 30. Zheng, D., Constantinidou, C., Hobman, J. L. & Minchin, S. D. Identification of the CRP regulon using in vitro and in vivo transcriptional profiling. Nucleic Acids Research 32, 5874–5893 (2004). 31. Busby, S. & Ebright, R. H. Transcription activation by catabolite activator protein (CAP). Journal of Molecular Biology 293, 199–213 (1999). 32. Tagami, H. & Aiba, H. Role of CRP in transcription activation at Escherichia coli lac promoter: CRP is dispensable after the formation of open complex. Nucleic Acids Research 23, 599–605 (1995). 33. Stevens, A. M., Dolan, K. M. & Greenberg, E. P. Synergistic binding of the Vibrio fischeri LuxR transcriptional activator domain and RNA polymerase to the lux promoter region. Proceedings of the National Academy of Sciences 91, 12619–12623 (1994). 34. Finney, A. H., Blick, R. J., Murakami, K., Ishihama, A. & Stevens, A. M. Role of the C-terminal domain of the alpha subunit of RNA polymerase in LuxR-dependent transcriptional activation of the lux operon during quorum sensing. J Bacteriol 184, 4520–4528 (2002). 35. Johnson, D. C., Ishihama, A. & Stevens, A. M. Involvement of region 4 of the σ70 subunit of RNA polymerase in transcriptional activation of the lux operon during quorum sensing. FEMS Microbiology Letters 228, 193–201 (2003). 36. Fang, C. et al. CueR activates transcription through a DNA distortion mechanism. Nat Chem Biol 17, 57–64 (2021). 37. Philips, S. J. et al. Allosteric transcriptional regulation via changes in the overall topology of the core promoter. Science 349, 877–881 (2015). 38. Chen, Y. et al. Tuning the dynamic range of bacterial promoters regulated by ligand-inducible transcription factors. Nat Commun 9, 64 (2018). 39. Razo-Mejia, M. et al. Tuning transcriptional regulation through signaling: a predictive theory of allosteric induction. Cell Systems 6, 456-469.e10 (2018). 40. Martin, R. G., Bartlett, E. S., Rosner, J. L. & Wall, M. E. Activation of the Escherichia coli marA/soxS/rob regulon in response to transcriptional activator concentration. Journal of Molecular Biology 380, 278–284 (2008). 41. Reichheld, S. E., Yu, Z. & Davidson, A. R. The induction of folding cooperativity by ligand binding drives the allosteric response of tetracycline repressor. Proceedings of the National Academy of Sciences 106, 22263–22268 (2009). 42. Brewster, R. C., Jones, D. L. & Phillips, R. Tuning promoter strength through RNA polymerase binding site design in Escherichia coli. PLoS Comput Biol 8, e1002811 (2012). 43. Zeng, W. et al. Rational design of an ultrasensitive quorum-sensing switch. ACS Synth. Biol. 6, 1445–1452 (2017). 44. Scholz, O., Köstner, M., Reich, M., Gastiger, S. & Hillen, W. Teaching TetR to recognize a new inducer. Journal of Molecular Biology 329, 217–227 (2003). 45. Rohlhill, J., Sandoval, N. R. & Papoutsakis, E. T. Sort-seq approach to engineering a formaldehyde-inducible promoter for dynamically regulated Escherichia coli growth on methanol. ACS Synthetic Biology 6, 1584–1595 (2017). 46. Lou, C., Stanton, B., Chen, Y.-J., Munsky, B. & Voigt, C. A. Ribozyme-based insulator parts buffer synthetic circuits from genetic context. Nat Biotechnol 30, 1137–1142 (2012). 47. Macdonald, L. E., Zhou, Y. & McAllister, W. T. Termination and slippage by bacteriophage T7 RNA polymerase. Journal of Molecular Biology 232, 1030–1047 (1993). 48. Thomsen, M. C. F. & Nielsen, M. Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion. Nucleic Acids Res 40, W281-287 (2012). 49. Bintu, L. et al. Transcriptional regulation by the numbers: models. Current Opinion in Genetics & Development 15, 116–124 (2005). 50. Kinney, J. B., Murugan, A., Callan, C. G. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl. Acad. Sci. U.S.A. 107, 9158–9163 (2010). 51. Estrem, S. T., Gaal, T., Ross, W. & Gourse, R. L. Identification of an UP element consensus sequence for bacterial promoters. Proc. Natl. Acad. Sci. U.S.A. 95, 9761–9766 (1998). 52. Van Brempt, M. et al. Predictive design of sigma factor-specific promoters. Nat Commun 11, 5822 (2020). 53. Mitchell, J. E. Identification and analysis of ‘extended -10’ promoters in Escherichia coli. Nucleic Acids Research 31, 4689–4695 (2003). 54. Zhu, Y. et al. Characterization of a minimal type of promoter containing the −10 element and a guanine at the −14 or −13 position in mycobacteria. Journal of Bacteriology 199, 10.1128/jb.00385-17 (2017). 55. Myers, K. S., Noguera, D. R. & Donohue, T. J. Promoter architecture differences among Alphaproteobacteria and other bacterial taxa. mSystems 6, 10.1128/msystems.00526-21 (2021). 56. Hook-Barnard, I. G. & Hinton, D. M. Transcription initiation by mix and match elements: flexibility for polymerase binding to bacterial promoters. Gene�Regul Syst Bio 1, 117762500700100020 (2007). 57. Yona, A. H., Alm, E. J. & Gore, J. Random sequences rapidly evolve into de novo promoters. Nat Commun 9, 1530 (2018). 58. Wade, J. T. & Grainger, D. C. Spurious transcription and its impact on cell function. Transcription 9, 182–189 (2018). 59. Singh, S. S. et al. Widespread suppression of intragenic transcription initiation by H-NS. Genes Dev. 28, 214–219 (2014). 60. Lloréns-Rico, V. et al. Bacterial antisense RNAs are mainly the product of transcriptional noise. Science Advances 2, e1501363 (2016). 61. Werner, F. & Grohmann, D. Evolution of multisubunit RNA polymerases in the three domains of life. Nat Rev Microbiol 9, 85–98 (2011). 62. Decker, K. B. & Hinton, D. M. Transcription regulation at the core: similarities among bacterial, archaeal, and eukaryotic RNA polymerases. Annu. Rev. Microbiol. 67, 113–139 (2013). 63. Stracy, M. et al. Transient non-specific DNA binding dominates the target search of bacterial DNA-binding proteins. Molecular Cell 81, 1499-1514.e6 (2021). 64. Choi, S. H. & Greenberg, E. P. The C-terminal region of the Vibrio fischeri LuxR protein contains an inducer-independent lux gene activating domain. Proceedings of the National Academy of Sciences 88, 11115–11119 (1991). 65. He, M.-Y. et al. Sensitive and specific cadmium biosensor developed by reconfiguring metal transport and leveraging natural gene repositories. ACS Sens. 6, 995–1002 (2021). 66. Guo, K.-H. et al. Determination of gold ions in human urine using genetically engineered microorganisms on a paper device. ACS Sens. 3, 744–748 (2018). 67. Kuo, S.-T. et al. Global fitness landscapes of the Shine-Dalgarno sequence. Genome Res. 30, 711–723 (2020). 68. Stanton, B. C. et al. Genomic mining of prokaryotic repressors for orthogonal logic gates. Nat Chem Biol 10, 99–105 (2014). 69. Vilanova, C. & Porcar, M. iGEM 2.0—refoundations for engineering biology. Nat Biotechnol 32, 420–424 (2014). 70. Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001). 71. Chou, H.-H., Delaney, N. F., Draghi, J. A. & Marx, C. J. Mapping the Fitness Landscape of Gene Expression Uncovers the Cause of Antagonism and Sign Epistasis between Adaptive Mutations. PLOS Genetics 10, e1004149 (2014). 72. Inman, H. F. & Bradley, E. L. The overlapping coefficient as a measure of agreement between probability distributions and point estimation of the overlap of two normal densities. Communications in Statistics - Theory and Methods 18, 3851–3874 (1989). 73. Kullback, S. Information Theory and Statistics. (Courier Corporation, 1997). 74. Einav, T. & Phillips, R. How the avidity of polymerase binding to the –35/–10 promoter sites affects gene expression. Proc Natl Acad Sci USA 116, 13340–13345 (2019). 75. Lagator, M. et al. Predicting bacterial promoter function and evolution from random sequences. eLife 11, e64543 (2022). 76. Jaynes, E. T. Probability Theory: The Logic of Science. (Cambridge University Press, 2003). 77. LaFleur, T. L., Hossain, A. & Salis, H. M. Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. Nat Commun 13, 5159 (2022). 78. Botev, Z. & Ridder, A. Variance reduction. in Wiley statsRef: statistics reference online 1–6 (John Wiley & Sons, Ltd, 2017). 79. Smoot, M. E., Ono, K., Ruscheinski, J., Wang, P.-L. & Ideker, T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27, 431–432 (2011). Chapter 4. 1. Lorenz, R. et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 6, 26 (2011). 2. Bintu, L. et al. Transcriptional regulation by the numbers: models. Curr. Opin. Genet. Dev. 15, 116–124 (2005). 3. Kinney, J. B., Murugan, A., Callan, C. G. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl. Acad. Sci. 107, 9158–9163 (2010). 4. Vera, J. M. et al. Genome-scale transcription-translation mapping reveals features of Zymomonas mobilis transcription units and promoters. mSystems 5, 10.1128/msystems.00250-20 (2020). 5. Reis, A. C. & Salis, H. M. An automated model test system for systematic development and improvement of gene expression models. ACS Synth. Biol. 9, 3145–3156 (2020). 6. LaFleur, T. L., Hossain, A. & Salis, H. M. Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. Nat. Commun. 13, 5159 (2022). | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92418 | - |
| dc.description.abstract | 基因表現始於基因轉錄成 mRNA，隨後 mRNA 被轉譯成蛋白質。順式調控元件（cis-regulatory element, CRE），如啟動子和核糖體結合位點（ribosomal binding site, RBS），分別決定轉錄和轉譯效率，並共同決定基因表現水平。建構功能性基因回路涉及 CRE 的耗時且反覆嘗試的優化，顯示對其序列-功能關係的理解仍不足。為了解決這個問題，在第二章中，我構建了49種RBS變體，在第三章中，我構建了412種啟動子變體，並進行了高通量實驗以測量它們的轉譯和轉錄效率。
將實驗數據與量化分析結合，我確定了三個一般性的設計原則：（1）RBS中Shine-Dalgarno序列的鳥嘌呤含量直接決定翻譯效率，儘管內源序列呈現腺嘌呤和鳥嘌呤富集的性質。（2）啟動子中的-10元件對於轉錄啟動是絕對必要的，而-35元件則不是。（3）儘管-35元件在功能上非必要，但其與RNA聚合酶的交互作用受轉錄因子調控。檢驗內源受調控的啟動子展示了一致的特性，表明這些啟動子受天擇精細地篩選。為了更深入地研究分子機制，在第二章中，我利用RNA二級結構演算法闡明了Shine-Dalgarno序列-功能關係，而在第三章中，我建構了生物物理模型來描述啟動子功能並量化RNA聚合酶和啟動子的結合能量。 我的論文強調全面的序列-功能映射的必要性，因為它提供了對 CRE 功能和演化完整的理解。這些數據集對於未來開發預測模型用以編程基因回路並識別細菌基因組中的內源 CRE 具有寶貴的價值。 | zh_TW |
| dc.description.abstract | Gene expression begins with transcription of genes into mRNA, followed by translation of mRNA into proteins. Cis-regulatory elements (CRE), such as promoters and ribosome binding sites (RBS), interact with the transcription and translation machinery, respectively, that jointly determine expression levels. Nevertheless, constructing a functional genetic circuit involves time-consuming and trial-and-error optimization of CRE, suggesting an insufficient understanding of their sequence-function relationship. To address this, I constructed 49 RBS variants (in Chapter 2) and 412 promoter variants (in Chapter 3) and conducted high-throughput experiments to characterize their translation and transcription efficiency, respectively.
Combining my experimental data with quantitative analysis and modeling, I identified three general design principles: (1) The guanine content of the Shine-Dalgarno sequence in RBS directly determines the translation efficiency, even though endogenous sequences show an AG-rich nature. (2) The -10 element in the promoter is absolutely essential for transcription initiation, whereas the -35 element is not. (3) Although the -35 element is functionally dispensable, its interaction with RNA polymerase (RNAP) is delicately modulated by transcriptional activators. Examining endogenous regulated promoters showed a consistent pattern, suggesting that regulatory gene expression has been fine-tuned by evolution. To delve deeper into the molecular mechanisms, in Chapter 2, I utilized an RNA folding algorithm to elucidate SD sequence-function relationship, while in Chapter 3, I developed biophysical models to describe promoter function and quantify RNAP-promoter binding energy. My work underscores the necessity of global sequence-function mapping as it provides an unbiased and comprehensive understanding of CRE function and evolution. These datasets are invaluable for future development of prediction models to program genetic circuits and identify endogenous CRE in bacterial genomes. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-03-22T16:24:58Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-03-22T16:24:58Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Chapter 1. Introduction ... 1
Chapter 2. Research Project ... 13 Global fitness landscapes of the Shine-Dalgarno sequence Published as: Kuo, S. T., Jahn, R. L., Cheng, Y. J., Chen, Y. L., Lee, Y. J., Hollfelder, F., ... & Chou, H. H. D. (2020). Global fitness landscapes of the Shine-Dalgarno sequence. Genome research, 30(5), 711-723. Abstract ... 15 Introduction ... 16 Results ... 18 Discussion ... 32 Methods ... 35 Data access ... 41 Acknowledgments ... 41 Author contributions ... 41 References ... 42 Supplemental Material ... 56 Chapter 3. Research Project ... 122 Design principles of bacterial promoters and transcriptional regulation Abstract ... 124 Introduction ... 124 Results ... 127 Discussion ... 134 Methods ... 135 References ... 146 Supplementary Information ... 156 Chapter 4. Conclusion ... 190 | - |
| dc.language.iso | en | - |
| dc.title | 高通量方法定量闡明細菌調節元件的設計原理 | zh_TW |
| dc.title | High-Throughput Approaches Quantitatively Elucidate the Design Principles of Bacterial Regulatory Elements | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 博士 | - |
| dc.contributor.oralexamcommittee | 廖本揚;陳詩允;陳昇宏;張家銘;吳亘承 | zh_TW |
| dc.contributor.oralexamcommittee | Ben-Yang Liao;See-Yeun Chen;Sheng-hong Chen;Jia-Ming Chang;Hsuan-Chen Wu | en |
| dc.subject.keyword | 順式調控元件,Shine-Dalgarno 序列,上位性,序列功能關係,微生物學,分子演化,細菌啟動子,轉錄調控,大規模平行報告分析,生物物理模型,合成生物學, | zh_TW |
| dc.subject.keyword | cis-regulatory element,Shine-Dalgarno sequence,epistasis,sequence-function relationship,microbiology,molecular evolution,bacterial promoter,transcriptional regulation,massively parallel reporter assays,biophysical model,synthetic biology, | en |
| dc.relation.page | 193 | - |
| dc.identifier.doi | 10.6342/NTU202304478 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2023-12-05 | - |
| dc.contributor.author-college | 生命科學院 | - |
| dc.contributor.author-dept | 生命科學系 | - |
| 顯示於系所單位： | 生命科學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-112-1.pdf 目前未授權公開取用 | 11.24 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。