研究生: |
汪冠霖 Wang, Guan-Lin |
---|---|
論文名稱: |
大腸桿菌內多套數質體受轉錄和細胞生理影響的聚集機制 Mechanisms of High-Copy-Number Plasmids Aggregation in Escherichia coli: Insights from Transcription and Cellular Physiology |
指導教授: |
張宜仁
Chang, Yi-Ren |
口試委員: |
張宜仁
Chang, Yi-Ren 周家復 Chou, Chia-Fu 游至仕 You, Jhih-Shih |
口試日期: | 2024/02/29 |
學位類別: |
碩士 Master |
系所名稱: |
物理學系 Department of Physics |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 48 |
中文關鍵詞: | 多套數質體 、聚集 、轉錄 、類核相關蛋白 |
英文關鍵詞: | High Copy Number plasmids, aggregation, Transcription, NAPs |
研究方法: | 實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202401650 |
論文種類: | 學術論文 |
相關次數: | 點閱:60 下載:1 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
目前對於多套數質體的聚集現象仍未出現完整的理論模型,我們試圖從轉錄與細胞生理的角度進行解釋。實驗結果表明質體上的轉錄強度雖影響了質體聚集,但並非導致聚集的主因。此外細胞內的基因表現量提升時在物理上導致了質體分布離散。我們於大腸桿菌BW25113中觀測ColE1衍生質體、pBR322。在活體細胞中ColE1質體傾向分佈於細胞的兩軸端點,且具有獨立於染色體排擠效應的聚集行為。對照在真核生物與染色體的組織研究,我們認為轉錄行為與細胞生理是導致質體聚集的可能原因,因此採取三種實驗:轉錄強度、轉錄因子數量與細胞狀態進行觀察。我們利用抑制子-操縱子(repressor- operator pair)專一性的阻斷質體上啟動子的轉錄,並使用FROS螢光標記質體的空間分佈,取得的質體分佈再以Ripley’s K function統計聚集程度。結果表明質體上的轉錄強度與轉錄因子並非導致質體聚集的主因,而兩者之間有複雜的關聯性。而另一方面,添加葡萄糖對質體的分佈的離散化是顯著且立即性的,從時間尺度上我們推測是基因表現提升在物理上的作用。此外隨細菌從快速生長期進入停滯期,質體的聚集強度增加,兩觀察顯示全細胞的基因表現強度有強烈影響。因此我們提出基於物理作用的NAPs互動模型,我們假定不具序列特異性的類核相關蛋白(NAPs)為使質體聚集的主因,其在空間中以橋接形成的三級結構即是質體聚集,並受轉錄的干擾而無法成型。
Currently, there’s still no comprehensive theoretical model for the High-Copy-Number plasmid aggregation. We attempt to explain it from the perspectives of transcriptional and cellular physiology effects. Experimental results indicate that transcriptional strength on the plasmid affects the plasmid’s aggregation but is the primary cause. Additionally, gene expression levels lead to the dispersal of plasmids.We observed ColE1-derived plasmids, pBR322 in Escherichia coli cell BW25113. pBR322 plasmids tend to distribute towards the endpoints of the cell, exhibiting aggregation behavior independent of Chromosome -Exclusion effects. Drawing comparisons with studies on eukaryotes and chromosome organization, we suggest that transcriptional behavior and cellular physiology may be potential causes of plasmid aggregation. Hence, 3 experiments were designed: Transcriptional strength inhibition, Transcription factors amount, and cellular physiology.Repressor-Operator pair on promoters specifically inhibit transcription from plasmids, and using Fluorescent repressor operator system (FROS) to visualize plasmid spatial distribution. The plasmid aggregation degree was then quantified using Ripley's K function. The results indicate that neither transcriptional intensity nor the transcription factors are the main cause of plasmid aggregation, also suggesting a complex theory behind this.On the other hand, glucose induces significant and immediate dispersion of plasmid distribution, indicating a physical effect of gene expression increase. Furthermore, as the transition from log growth to stationary phase, plasmids become more aggregation, indicating a strong influence of the gene expression level from whole-cell. Therefore, we propose a physical interaction model based on Nucleoid-Associated Proteins (NAPs), assuming that non-sequence-specific NAPs are the primary cause of plasmid aggregation. NAP tertiary structure bridging in space results in plasmid aggregation, which is disrupted by gene expression.
[1] Eliasson, Å., et al., Direct visualization of plasmid DNA in bacterial cells. Molecular microbiology, 1992. 6(2): p. 165-170
[2] Pogliano, J., Ho, T. Q., Zhong, Z., & Helinski, D. R. (2001). Multicopy plasmids are clustered and localized in Escherichia coli. Proceedings of the National Academy of Sciences of the United States of America, 98(8), 4486–4491.
[3] Yao, S., Helinski, D. R., & Toukdarian, A. (2007). Localization of the naturally occurring plasmid ColE1 at the cell pole. Journal of Bacteriology, 189(5), 1946–1953.
[4] Yao, S., D.R. Helinski, and A. Toukdarian, Localization of the naturally occurring plasmid ColE1 at the cell pole. Journal of bacteriology, 2007. 189(5): p. 1946-1953
[5] Papantonis A., Kohro T.(2012). TNFα signals through specialized factories where responsive coding and miRNA genes are transcribed. EMBO J.; 31:4404–4414.
[6] Hsu, T. M., & Chang, Y. R. (2019). High-Copy-Number plasmid Segregation—Single-Molecule dynamics in single cells. Biophysical Journal, 116(5), 772–780.
[7] Frenkiel-Krispin, D., Ben-Avraham, I., Englander, J., Shimoni, E., Wolf, S. G., & Minsky, A. (2004). Nucleoid restructuring in stationary‐state bacteria. Molecular Microbiology, 51(2), 395–405.
[8] Luijsterburg, M. S., Noom, M. C., Wuite, G. J. L., & Dame, R. T. (2006). The architectural role of nucleoid-associated proteins in the organization of bacterial chromatin: A molecular perspective.
[9] Cook, P. R., & Marenduzzo, D. (2018). Transcription-driven genome organization: A model for chromosome structure and the regulation of gene expression tested through simulations. Nucleic Acids Research, 46(19), 9895-9906.
[10] Ulianov, S. V., Khrameeva, E., Гаврилов, А. В., Flyamer, I. M., Kos, P., Mikhaleva, E. A., Penin, A. A., Logacheva, M. D., Imakaev, M., Chertovich, A. V., Gelfand, M. S., Shevelyov, Y. Y., & Razin, S. V. (2015). Active chromatin and transcription play a key role in chromosome partitioning into topologically associating domains. Genome Research, 26(1), 70–84.
[11] Cagliero, C. (2015). The dynamic nature and territory of transcriptional machinery in the bacterial chromosome. Frontiers in Microbiology, 6.
[12] Enjalbert, B., Létisse, F., & Portais, J. (2013). Physiological and Molecular Timing of the Glucose to Acetate Transition in Escherichia coli. Metabolites, 3(3), 820–837.
[13] Summers, D.K. and D.J. Sherratt, Multimerization of high copy number plasmids causes instability: ColE 1 encodes a determinant essential for plasmid monomerization and stability. Cell, 1984. 36(4): p. 1097-1103.
[14] Kiskowski, M. A., Hancock, J. F., & Kenworthy, A. K. (2009). On the use of Ripley's K-function and its derivatives to analyze domain size. Biophysical Journal, 97(4), 1095-1103.
[15] Ruan, Y., Yin, P., Li, F., Li, D., Lin, Q., & Li, K. (2019). The accuracy of determining cluster size by analyzing Ripley’s K function in single molecule localization microscopy. Applied Sciences, 9(16), 3271.
[16] Kiskowski, M. A., Hancock, J. F., & Kenworthy, A. K. (2009). On the Use of Ripley’s K-Function and Its Derivatives to Analyze Domain Size. Biophysical Journal, 97(4), 1095–1103.
[17] Amgad, M., Itoh, A., & Tsui, M. M. (2015). Extending Ripley’s K-function to quantify aggregation in 2-D grayscale images. PLOS ONE, 10(12), e0144404.
[18] Lagache, T., Lang, G., Sauvonnet, N., & Olivo‐Marin, J. (2013). Analysis of the Spatial Organization of Molecules with Robust Statistics. PLOS ONE, 8(12), e80914.