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  1. NTU Theses and Dissertations Repository
  2. 理學院
  3. 物理學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73446
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dc.contributor.advisor朱士維(Shi-Wei Chu)
dc.contributor.authorHan-Yuan Linen
dc.contributor.author林涵源zh_TW
dc.date.accessioned2021-06-17T07:35:21Z-
dc.date.available2019-06-05
dc.date.copyright2019-06-05
dc.date.issued2019
dc.date.submitted2019-04-30
dc.identifier.citation1.Shimomura, O., Saiga, Y. & Johnson, F.H. PURIFICATION AND PROPERTIES OF AEQUORIN, A BIO- (CHEMI-) LUMINESCENT PROTEIN FROM JELLY-FISH, AEQUOREA AEQUOREA. Federation Proceedings 21, 401-& (1962).
2.Chalfie, M., Tu, Y., Euskirchen, G., Ward, W.W. & Prasher, D.C. GREEN FLUORESCENT PROTEIN AS A MARKER FOR GENE-EXPRESSION. Science 263, 802-805 (1994).
3.Huang, B., Babcock, H. & Zhuang, X. Breaking the Diffraction Barrier: Super-Resolution Imaging of Cells. Cell 143, 1047-1058 (2010).
4.Chen, F., Tillberg, P.W. & Boyden, E.S. Expansion microscopy. Science 347, 543-548 (2015).
5.Chang, J.B., et al. Iterative expansion microscopy. Nat. Methods 14, 593-+ (2017).
6.Ku, T., et al. Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues. Nat. Biotechnol. 34, 973-+ (2016).
7.Klar, T.A., Jakobs, S., Dyba, M., Egner, A. & Hell, S.W. Fluorescence microscopy with diffraction resolution barrier broken by stimulated emission. Proceedings of the National Academy of Sciences of the United States of America 97, 8206-8210 (2000).
8.Gustafsson, M.G.L. Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. Journal of Microscopy-Oxford 198, 82-87 (2000).
9.Hess, S.T., Girirajan, T.P.K. & Mason, M.D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophysical Journal 91, 4258-4272 (2006).
10.Rust, M.J., Bates, M. & Zhuang, X.W. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793-795 (2006).
11.Uno, S.-n., et al. A spontaneously blinking fluorophore based on intramolecular spirocyclization for live-cell super-resolution imaging. Nat. Chem. 6, 681-689 (2014).
12.Vaziri, A., Tang, J., Shroff, H. & Shank, C.V. Multilayer three-dimensional super resolution imaging of thick biological samples. Proc. Natl. Acad. Sci. U.S.A. 105, 20221-20226 (2008).
13.Schropp, M., Seebacher, C. & Uhl, R. XL-SIM: Extending Superresolution into Deeper Layers. Photonics 4, 33 (2017).
14.Deka, G., et al. Resolution enhancement in deep-tissue nanoparticle imaging based on plasmonic saturated excitation microscopy. Apl Photonics 3 (2018).
15.Liu, Y.C. & Chiang, A.S. High-resolution confocal imaging and three-dimensional rendering. Methods 30, 86-93 (2003).
16.Takasaki, K.T., Ding, J.B. & Sabatini, B.L. Live-Cell Superresolution Imaging by Pulsed STED Two-Photon Excitation Microscopy. Biophys. J. 104, 770-777 (2013).
17.Schnorrenberg, S., et al. In vivo super-resolution RESOLFT microscopy of Drosophila melanogaster. Elife 5, e15567 (2016).
18.Yu, W.T., et al. Super-resolution deep imaging with hollow Bessel beam STED microscopy. Laser Photon. Rev. 10, 147-152 (2016).
19.Ke, M.-T., et al. Super-Resolution Mapping of Neuronal Circuitry With an Index-Optimized Clearing Agent. Cell Rep. 14, 2718-2732 (2016).
20.Urban, N.T., Willig, K.I., Hell, S.W. & Nagerl, U.V. STED Nanoscopy of Actin Dynamics in Synapses Deep Inside Living Brain Slices. Biophys. J. 101, 1277-1284 (2011).
21.Yamanaka, M., et al. Saturated excitation microscopy for sub-diffraction-limited imaging of cell clusters. J. Biomed. Opt. 18, 126002 (2013).
22.Lee, J., Miyanaga, Y., Ueda, M. & Hohng, S. Video-Rate Confocal Microscopy for Single-Molecule Imaging in Live Cells and Superresolution Fluorescence Imaging. Biophys. J. 103, 1691-1697 (2012).
23.Zanacchi, F.C., et al. Live-cell 3D super-resolution imaging in thick biological samples. Nat. Methods 8, 1047-1049 (2011).
24.Qian, J., et al. Full-color structured illumination optical sectioning microscopy. Scientific Reports 5 (2015).
25.Sun, B.S., Salter, P.S. & Booth, M.J. Effects of aberrations in spatiotemporal focusing of ultrashort laser pulses. Journal of the Optical Society of America a-Optics Image Science and Vision 31, 765-772 (2014).
26.Rowlands, C.J., Bruns, O.T., Bawendi, M.G. & So, P.T.C. Objective, comparative assessment of the penetration depth of temporal-focusing microscopy for imaging various organs. Journal of Biomedical Optics 20 (2015).
27.Thompson, R.E., Larson, D.R. & Webb, W.W. Precise nanometer localization analysis for individual fluorescent probes. Biophysical Journal 82, 2775-2783 (2002).
28.Quan, T.W., Zeng, S.Q. & Huang, Z.L. Localization capability and limitation of electron-multiplying charge-coupled, scientific complementary metal-oxide semiconductor, and charge-coupled devices for superresolution imaging. Journal of Biomedical Optics 15 (2010).
29.van de Linde, S., et al. Direct stochastic optical reconstruction microscopy with standard fluorescent probes. Nature Protocols 6, 991-1009 (2011).
30.Folling, J., et al. Fluorescence nanoscopy by ground-state depletion and single-molecule return. Nature Methods 5, 943-945 (2008).
31.Deschout, H., et al. Precisely and accurately localizing single emitters in fluorescence microscopy. Nature Methods 11, 253-266 (2014).
32.Ando, R., Hama, H., Yamamoto-Hino, M., Mizuno, H. & Miyawaki, A. An optical marker based on the UV-induced green-to-red photoconversion of a fluorescent protein. Proc. Natl. Acad. Sci. U.S.A. 99, 12651-12656 (2002).
33.Mertz, J. & Kim, J. Scanning light-sheet microscopy in the whole mouse brain with HiLo background rejection. Journal of Biomedical Optics 15 (2010).
34.Pai, T.P., et al. Drosophila ORB protein in two mushroom body output neurons is necessary for long-term memory formation. Proc. Natl. Acad. Sci. U.S.A. 110, 7898-7903 (2013).
35.Dubnau, J., et al. The staufen/pumilio pathway is involved in Drosophila long-term memory. Curr. Biol. 13, 286-296 (2003).
36.Ovesny, M., Krizek, P., Borkovec, J., Svindrych, Z.K. & Hagen, G.M. ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging. Bioinformatics 30, 2389-2390 (2014).
37.Huang, B., Wang, W.Q., Bates, M. & Zhuang, X.W. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810-813 (2008).
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73446-
dc.description.abstract了解神經網絡的分布有助於知道在腦中的神經如何連結、甚至如何運作的,但是神經纖維相當細緻,又會彼此纏繞形成複雜結構,用傳統顯微鏡非常不容易分辨出來。比方說,神經的樹突纖維可以小到100奈米的寬度,而當兩條纖維彼此緊靠,我們需要20奈米的解析度才能分辨(假設細胞膜厚度10奈米,螢光表現在細胞質)。更困難的地方是這些細緻的神經纖維會在三度空間的腦組織中延伸很遠,連結到遠方的神經。所以若想要清楚的分析神經網路,我們不只需要高解析度,還需要這個解析度能夠維持穿透整個腦的深度。
因為繞射的限制,光學系統的最佳解析度大約為激發波長的一半,以可見光來說就是約250奈米。2014年的諾貝爾化學獎頒給了三位科學家,他們致力於發展可以突破繞射極限的超解析顯微術。其中,定位顯微術只需要接收到100個光子,就可以把螢光分子的位置定位到接近20奈米。因此,若需要20奈米解析度,螢光定位顯微術會是最好的選擇。
但要在腦中使用定位顯微術會遭遇到三個困難。第一是對比,定位顯微術需要能夠不斷閃爍的對比劑,而基因轉殖的螢光蛋白比較容易標記整個腦組織,但是普通的螢光蛋白只會發出強度固定的螢光,並不會閃爍,而且存在著光漂白(Photo-bleach)的問題;第二是廣域照射(Wide-field)的定位顯微術缺乏光切片(Optical sectioning)的能力,沒辦法區辨不同層的訊號,所以一般定位顯微術被侷限在數個微米的深度內;第三是來自組織的像差、散射也同樣會限制影像深度。
因此,我們結合四個關鍵的技術:一、以定位顯微術提升解析度;二、使用還原劑(ME)來使基因轉殖、可以光轉換的螢光蛋白閃爍,並在其被光漂白後,利用光轉換來補充螢光蛋白;三、利用轉盤共軛焦顯微鏡提供光切片的能力;四、使用光學澄清減少組織的散射與像差。藉此,在果蠅腦從上到下的任何位置都取得20奈米超解析影像。而且藉由這個方法,我們可以解決一開始提出的問題:區辨兩團靠得很近的樹突纖維,甚至以三維重組呈現它在空間中的走向。
zh_TW
dc.description.abstractTo understand brain function, detailed anatomical mapping of neurons and their fiber distributions should be the first step. However, it is not an easy task since neuronal network is composed of tiny fibers that may closely entangle with each other. For example, the diameter of a dendrite in Drosophila brain can be as small as 100 nm, and when dendritic fibers interweave with each other, at least 20-nm resolution would be necessary to resolve these fibers (assuming fluorescent protein expressed in cytoplasm, and the thickness of a cellular membrane is 10 nm). What makes it even more difficult is that these fibers may extend three dimensionally throughout a brain, so we need not only a high-resolution technique, but also a technique that is able to penetrate the whole brain to track neuronal fibers.
Because of diffraction limit, the resolution of an optical microscope is confined around λ/2, which is roughly equal to 250 nm for visible light. Nobel Prize in Chemistry 2014 was awarded to three scientists due to their contribution on “superresolution microscopy” that is able to break the diffraction barrier. Among all superresolution techniques, localization microscopy achieves one order resolution enhancement by detection of >100 photons from each fluorescent protein (FP). Thus, to reach 20-nm resolution, localization microscopy should be the best option.
Nevertheless, to apply localization microscopy across a whole brain, there are three major challenges. First, localization microscopy requires a “blinking” contrast agent. Generally speaking, genetically encoded FP is used when labeling a thick brain tissue. However, blinking FP is scarce, while suffered from photo-bleaching. Second, due to lack of optical sectioning ability, wide-field-based localization microscopy cannot distinguish signals from different layers and thus imaging depth is confined to less than 10 μm. Third, tissue-induced scattering and aberration also limit the imaging depth.
In this study, we combine four techniques to achieve 20-nm superresolution across a whole Drosophila brain, including 1. localization microscopy to enhance resolution; 2. adding ME to enable blinking of genetically encoded, photo-convertible FP. Furthermore, we can use photo-conversion to supply the bleached FP; 3. spinning disk confocal microscope to provide optical sectioning; 4. tissue clearing to minimize tissue scattering/aberration. We name this combination COOL, i.e. spinning disk COnfocal lOcalization with tissue cLearing. COOL allows us to distinguish 3D entangled dendrites even at the bottom of the brain, paving the way toward whole-brain neural network analysis.
en
dc.description.provenanceMade available in DSpace on 2021-06-17T07:35:21Z (GMT). No. of bitstreams: 1
ntu-108-R04222050-1.pdf: 3988408 bytes, checksum: 4d73b7c3668d575f8bbc1630a6b302b5 (MD5)
Previous issue date: 2019
en
dc.description.tableofcontentsChapter 1. Introduction 13
1.1 Imaging parameters: contrast, resolution, and imaging depth 13
1.2 Optical sectioning: The axial contrast of superresolution microscopy 16
1.3 Tissue-induced aberration and scattering: The imaging depth of superresolution microscopies 17
1.4 Review of current deep-tissue superresolution techniques 19
1.4.1 Point-scanning based 20
1.4.2 Wide-field based 22
1.4.3 Expansion methods 23
1.4.4 Brief summary 25
Chapter 2. Principle 26
2.1 Localization microscopy 26
2.1.1 How does localization microscopy break the diffraction limit? 26
2.1.2 How do localization images form? 27
2.1.3 How do fluorophores blink? 29
2.2 Optical sectioning – spinning disk confocal microscope 32
2.3 Brief summary 33
Chapter 3. Instrument and Sample 34
3.1 Microscope component 34
3.2 Sample preparation 34
3.2.1 Fly stocks 34
3.2.2 Brain sample preparation 35
Chapter 4. Experimental procedures and image process 36
4.1 Imaging condition 36
4.1.1 Wavelength 36
4.1.2 Laser power and exposure time 36
4.2 Data processing 37
4.2.1 Software 37
4.2.2 Confocal image 37
4.2.3 Free online localization processing program: ThunderSTORM 37
4.2.4 Manual image segmentation (3D neuron tracking) 39
Chapter 5. Result and discussion 39
5.1 Imaging depth enhancement by tissue clearing 39
5.2 Elimination of background by spinning disk confocal microscope 40
5.3 Performance of COOL in deep tissue 41
5.4 COOL on dendritic fibers 44
5.5 3D reconstruction 46
5.6 The axial resolution of localization microscopy 49
5.6.1 The principle of astigmatism localization 49
5.6.2 The PSF test of astigmatism localization 50
5.6.3 Theoretical calculation of astigmatic PSF size 51
5.6.4 Astigmatism localization in a Drosophila brain 53
5.7 Convertible property of Kaede 54
Chapter 6. Discussion 57
6.1 Depth limitation 57
6.2 Comparison of spinning disk confocal microscope and light sheet 57
6.3 Incomplete segmentation 58
6.4 Astigmatism localization 59
Chapter 7. Conclusion and Perspective 60
7.1 Conclusion 60
7.2 Perspective 60
Chapter 8. Reference 62
dc.language.isoen
dc.subject神經網路zh_TW
dc.subject光學澄清zh_TW
dc.subject轉盤共軛焦顯微鏡zh_TW
dc.subject定位顯微術zh_TW
dc.subject深組織中的超解析顯微術zh_TW
dc.subjectneuronal networken
dc.subjectdSTORMen
dc.subjectspinning disk confocal microscopeen
dc.subjecttissue clearingen
dc.subjectdeep-tissue superresolutionen
dc.subjectlocalization microscopyen
dc.title以20奈米解析度觀察果蠅全腦神經網路zh_TW
dc.titleObserving neuronal network across the whole brain of Drosophila with ~20 nm resolutionen
dc.typeThesis
dc.date.schoolyear107-2
dc.description.degree碩士
dc.contributor.oralexamcommittee江安世(Ann-Shyn Chiang),林彥穎(Yen-Yin Lin),朱麗安(Li-An Chu),林耿慧(Keng-Hui Lin)
dc.subject.keyword定位顯微術,轉盤共軛焦顯微鏡,光學澄清,深組織中的超解析顯微術,神經網路,zh_TW
dc.subject.keywordlocalization microscopy,dSTORM,spinning disk confocal microscope,tissue clearing,deep-tissue superresolution,neuronal network,en
dc.relation.page65
dc.identifier.doi10.6342/NTU201900735
dc.rights.note有償授權
dc.date.accepted2019-05-01
dc.contributor.author-college理學院zh_TW
dc.contributor.author-dept物理學研究所zh_TW
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