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Study of biomolecular interactions in vivo by multicolour fluorescence spectroscopy

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STUDY OF BIOMOLECULAR INTERACTIONS IN VIVO BY MULTICOLOUR FLUORESCENCE SPECTROSCOPY FOO YONG HWEE (B.Sc.(Hons.), NUS) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF CHEMISTRY NATIONAL UNIVERSITY OF SINGAPORE 2011 This work was performed in the Department of Chemistry at the National University of Singapore under the supervision of Associate Professor Thorsten Wohland, and in the Institute of Medical Biology, Agency for Science, Technology and Research, under the co-supervision of Associate Professor Sohail Ahmed, between August 2006 to July 2011. The translocation project of p21 and PCNA was done in collaboration with Dr Carsten Schultz in the European Molecular Biology Laboratory (Heidelberg), between October 2009 to January 2010. Part of the PIEFCCS measurements was performed in Ludwig-Maximilians-Universität München in collaboration with Professor Don C. Lamb in December 2009. The results have been partly published in  Y. H. Foo, V. Korzh, and T. Wohland. Fluorescence Correlation and CrossCorrelation Spectroscopy Using Fluorescent Proteins for Measurements of Biomolecular Processes in Living Organisms. 2011. Springer Series on Fluorescence, Online FirstTM, 31 March 2011.  Shi, X., Y. H. Foo, T. Sudhaharan, S. W. Chong, V. Korzh, S. Ahmed, and T. Wohland. 2009. Determination of dissociation constants in living zebrafish embryos with single wavelength fluorescence cross-correlation spectroscopy. Biophys J 97:678-686.  Sudhaharan, T., P. Liu, Y. H. Foo, W. Bu, K. B. Lim, T. Wohland, and S. Ahmed. 2009. Determination of in vivo dissociation constant, KD, of Cdc42-effector complexes in live mammalian cells using single wavelength fluorescence crosscorrelation spectroscopy. J Biol Chem 284:13602-13609. Foo Yong Hwee 17/08/2011 i Acknowledgements I started off with only an analytical chemistry background. Thus, this thesis in the field of biophysics would not be possible without the help of many individuals. I would like to express my special thanks to my supervisor Associate Professor Thorsten Wohland for the opportunities to work in these projects. The support, guidance, patience and freedom he has given me are greatly appreciated. I have gained a lot from his passion for research and his eye for details. I am very grateful to my co-supervisor Associate Professor Sohail Ahmed for making me a part of his lab and showing me the ropes of molecular cell biology. As I have spent most of my time in his lab, I am lucky to have his support, patience and guidance. I have learned a great deal about molecular biology and imaging from the numerous discussions with him. I am greatly thankful to Professor Ernst H. K. Stelzer for hosting me during my short-term EMBO fellowship in the European Molecular Biology Laboratory (EMBL). I would like to thank Dr Carsten Schultz and the technical assistance given by Dr Alan Piljic and Dr Malte Wachsmuth in the EMBL for the project during the stay. I am grateful for the collaboration and support given by Professor Don C. Lamb of Ludwig-Maximilians-Universität München during my short stay in his lab. Special thanks to Nikolaus Naredi-Rainer and Dr Matthias Höller, for setting up the instruments during that period. I wish to thank all the colleagues from the Biophysical Fluorescence Laboratory in the National University of Singapore and from the Neural Stem Cells group in the Institute of Medical Biology for their discussions, guidance, patience and friendship. In particular, Dr Liu Ping for the guidance in SW-FCCS; Dr Shi Xianke for the zebrafish embryo measurements; Dr Thankiah Sudhaharan and Dr Eric Lam Chen Sok for the guidance and discussion in molecular cell biology. Last but not least, I would like to thank my parents for their love, support and understanding. ii Table of Contents Acknowledgements . ii Summary vii List of Tables ix List of Figures .x Lists of Symbols and Acronyms xii Introduction .1 Theory and Instrumental Setup 11 2.1. Fluorescence Correlation Spectroscopy (FCS) .13 2.1.1. Fluorescence fluctuations . 13 2.1.2. The Autocorrelation function . 14 2.1.3. Theoretical ACF models 15 2.2. Fluorescence Cross-Correlation Spectroscopy (FCCS) 23 2.2.1. The Cross-Correlation Function 24 2.3. Applying FCS and FCCS in vivo 27 2.3.1. Background corrections . 27 2.3.2. Crosstalk 30 2.3.3. Optimizing measurement conditions . 31 2.4. Instrument Setup and SW-FCCS 31 iii Quantitation Using Cross-Correlation Ratios: A Simulation Study 34 3.1. Introduction .34 3.2. Materials and Method .36 3.3. Cross-correlation ratios for 1:1 binding 37 3.4. Quantitation for a dimerization system .41 3.5. Summary .43 Determination of Dissociation Constants in Living Cells 45 4.1. Interaction of Cdc42 with IQGAP1 in living cells and zebrafish embryo. 47 4.1.1 Theory . 47 4.1.2. Cell culture . 49 4.1.3. Plasmids . 49 4.1.4. Instrumentation and data analysis 50 4.1.5. FCCS Calibration . 50 4.1.6. Controls 52 4.1.7. Interaction of Cdc42T17N with IQGAP1 . 53 4.1.8. Interaction of Cdc42G12V with IQGAP1 . 54 4.1.9. Comparison of the results in CHO cells and zebrafish embryos . 56 4.1.10 Conclusion 58 4.2. Interaction of p21 with PCNA in Living Cells with FCCS and Translocation 59 iv 4.2.1 Introduction . 59 4.2.2 FCCS Instrumentation 60 4.2.3. Plasmids and cell culture . 60 4.2.4. Translocation 61 4.2.5. FCCS measurements 62 4.2.6 Conclusion 63 Factors Affecting Fluorescence Cross-Correlation Spectroscopy 65 5.1. Introduction .65 5.2. Theory .66 5.2.1. Cross-correlation volume . 66 5.2.2. CCF ratios 68 5.2.3. Pulsed interleave excitation-FCCS and FRET . 69 5.3. Materials and Methods 71 5.3.1. Plasmids and cell cultures 71 5.3.2. Cycloheximide chase experiment 72 5.3.3. SW-FCCS Instrumentation 72 5.3.4. Obtaining the brightnesses of GFP dimers 72 5.3.5. Pulsed interleave excitation-FCCS Instrumentation 73 5.4. Results and Discussions 74 5.4.1. Calibration of SW-FCCS observation volumes with a single dye.74 v 5.4.2. Photophysical properties of tandem FPs change the auto- and cross-correlation amplitudes 75 5.4.3. Non-fluorescent FPs and their influence on the FCCS data 79 5.4.4. Influence of FRET on the amplitudes 83 5.4.5. Determination of effective observation volumes and correction parameters 85 5.4.6. Influence of non-fluorescent labels on binding experiments . 87 5.4.7. Influence of endogenous labels on binding experiments . 90 5.4.8. Experimental Kd (mRFP against mCherry) . 93 5.4.9. Experimental Kd with endogenous proteins . 94 5.5. Conclusion 95 Conclusion and Outlook .97 Bibliography .102 vi Summary Fluorescence correlation spectroscopy (FCS) and its modality fluorescence crosscorrelation spectroscopy (FCCS) are single molecule sensitive optical tools to study mobility, concentrations and interactions. Due to their non-invasive nature, they are gaining popularity in studying molecular processes in vivo. The aim of this thesis is to apply and develop single-wavelength-FCCS (SW-FCCS), a variant of FCCS, to study protein-protein interactions in vivo. The thesis is organized into the following chapters: Chapter starts with discussing the importance of green florescent proteins (GFP) in modern cell biology. The advent of GFP led to the development of many optical tools to study molecular interactions and dynamics in vivo. A review of the different modalities of FCS/FCCS is presented and what are the different types of GFP mutants that are commonly used in FCCS. Chapter introduces the principles and instrumental setup of FCS and FCCS. It discusses the additional corrections and conditions when applied in vivo. Chapter discusses the cross-correlation ratios, which is commonly used to quantitate binding. It was shown, using a series of simulations, that these crosscorrelation ratios are dependent on the Kd of the binding, concentration range and the relative amount of red to green labeled molecules in the system. Chapter applies SW-FCCS to quantitate protein-protein interactions. It is divided into two parts. In the first part, the binding between a small GTPases protein vii Cdc42, and one of its effectors, IQGAP1, is investigated. The Kd of the binding in cell culture was compared with that in zebrafish embryo. In the second part, SW-FCCS is applied to study interaction between two proteins, p21 and PCNA, which are involved in DNA replication and DNA damage repair. Chapter addresses issues which constantly surface during measurements in vivo but are not studied extensively. These issues include mismatch in effective volumes, non-fluorescent fluorescent labels, FRET, photobleaching and endogenous proteins. All these factors influence the quality of the determined Kd. Major findings include quantitating the fraction of non-fluorescent red fluorescent proteins (mRFP and mCherry) and investigating the relationship of Kd with non-fluorescent labels both by simulations and experiments. Chapter concludes and presents outlook for future FCS and FCCS research. viii List of Tables 4.1 Summary of FCCS study in zebrafish muscle fiber and CHO cells 57 5.1 SW-FCCS measurements of different tandem fluorescent proteins 78 ix Chapter Despite being able to determine the Kds of interactions, discrepancies were observed. In theory, the tandem FPs should result in a cross-correlation ratio of 1. However, measurements to date by us and others achieved only a ratio of ~0.5. In chapter 5, it was demonstrated that this non-ideal ratio is due to imperfect overlap of effective volumes and can be corrected. From measurements of different tandem FPs, it was shown that the ratio is also dependent on the type of FPs and FRET. This leads to the finding that a large fraction of mRFP (78 %) and mCherry (60%) was found to be non-fluorescent hence affecting the quantitation of the amount of red labeled molecules. Due to this issue, the quality of the Kd was compromised. Endogenous proteins also act as a form of non-detected molecule which competes for binding. The effect of these was studied using Kd simulations followed by experiments using either mRFP or mCherry labeled Cdc42 and in the presence or absence of unlabeled Cdc42 (to mimic endogenous proteins). As the amount of fluorescent mRFP and mCherry are very different, the Kds determined for mRFP/mCherry-Cdc42 binding to EGFPIQGAP1 showed very different results. However, when the fraction of nonfluorescent FPs is taken into account, the Kds for both experiments becomes similar, indicating that non-fluorescent labels can be accounted for. In summary, chapter showed that the quantity of FCCS measurements is dependent on photobleaching, selection of the FPs, FRET and overlap of the effective volumes, and that these factors can be accounted for. Only by understanding these issues can the technique be developed further. 99 Chapter 6.2 Outlook In this thesis, the capabilities and limitations of FCCS were shown. It is a powerful tool to determine molecular interaction in live cells and organisms. However, the technique remains largely inaccessible to most biological laboratories. Although there are commercial systems available, they are not as ubiquitously available as other biophysical techniques. Commercial systems only provide basic data treatment and are mainly based on confocal FCS/FCCS. The more advanced applications or systems, such as scanning or camera based FCS/FCCS, are not yet commercialized or require special modification to the commercial system which is only possible in specialized laboratories. This is because many modalities of FCS/FCCS are still being developed and are usually used by only a few groups around the world. These new FCS modalities often require self-written software packages, require newly developed data treatment algorithms, and need handling and maintenance by specialists. In addition, the mathematical concepts involved in FCS/FCCS are not trivial for new comers who wish to use the technique. Hence, very often, collaborations between biological laboratories and laboratories specialized in biophysical techniques are required. FCCS is an extension of FCS. Future developments in FCS will impact the way FCCS can be applied. Some new FCS modalities such as the combination of stimulated emission depletion (STED) with FCS (STED-FCS) can reduce the diffraction limited volume allowing higher concentration and smaller region to be measured [166]. FCS has also been used with nearfield scanning optical microscopy [167], nano-apertures [168] and supercritical angle illumination [169] to manipulate the observation volume. Fluorescence lifetime correlation spectroscopy (FLCS), 100 Chapter where contributions due to different fluorescent species can be separated based on their lifetime and not emission wavelengths, is able to generate ACF free from unwanted background fluorescence or individual ACFs from spectrally similar fluorescent species as long as their fluorescence lifetime can be resolved [106, 108]. It can also separate particles with similar diffusion time, something which the conventional FCS cannot achieve. FLCS has been applied to living cells very recently [170]. Optical fiber-based FCS has also been developed [171-174]. Although these studies were performed in solution, optical fiber based FCS has the potential of measuring in remote areas of an organism. The initial motivation of applying FCS or single molecule techniques in live cells or organisms is its physiological relevance. Techniques which induce high amount of laser radiation thus inducing photodamage and phototoxicity, or require extensive physical manipulation of the organism to the point that they are no longer physiological relevant should be avoided. Ideally, the measurement should be as noninvasive and use the lowest amount of radiation per photon detected as possible. Light-sheet based illumination as used in SPIM-FCS, greatly enhances the multiplexing capabilities of FCS, allowing the measurements of whole areas in an organism simultaneously with greatly reduced phototoxicity [82, 175]. This allows capturing many more measurements per organism and makes it possible to establish FCS/FCCS images in which each pixel reports not on the fluorescence intensity but on molecular parameters, including molecular mobility, concentration, and degree of biomolecular interactions. A similar technique which uses image correlation concept is raster image correlation spectroscopy (RICS) [176, 177]. RICS uses the images acquired from a confocal laser scanning microscope to perform correlations instead of using a separate 101 Chapter FCS module. The fluorescence intensity in one of the pixels is considered to be a single point measurement which can be spatially and/or temporally correlated. RICS exploits the time structure hidden during the acquisition of an image to allow one to monitor processes in the microseconds to seconds timescale. Looking at the way how single-molecule experiments are done nowadays, if properly designed, the photons collected from one single experiment can actually be used by a number of techniques to extract information. Apart from FCS/FCCS, one can perform single-molecule FRET [160], FLCS [106, 108], FLIM-FRET [170, 178] or photon counting histograms [161, 162, 179] on a single instrument and experiment. This will maximize the amount of information acquired per experiment. As GFPs and its variants are probably going to be the preferred choice of reporters for biological studies in the future, understanding their photophysical properties will be helpful not only in FCS but in many other single molecule sensitive techniques. Although many new FPs have been generated in recent years [180, 181], the wait continues for a brighter and more stable RFP than mCherry. Going hand in hand with the advances in FPs, advances in technologies such as better detectors and optical systems, more efficient data treatment and computing power are constantly being developed. Studies with higher spatial and temporally resolution can be expected in the future. With the wealth of quantitative information FCS and FCCS can generate, they are powerful techniques to be applied in vivo to study molecular processes inaccessible by many other techniques. 102 Bibliography 1. Shimomura, O., F.H. Johnson, and Y. Saiga, Extraction, purification and properties of aequorin, a bioluminescent protein from the luminous hydromedusan, Aequorea. J Cell Comp Physiol, 1962. 59: p. 223-39. 2. Chalfie, M., et al., Green fluorescent protein as a marker for gene expression. Science, 1994. 263(5148): p. 802-5. 3. Heim, R., A.B. Cubitt, and R.Y. Tsien, Improved green fluorescence. Nature, 1995. 373(6516): p. 663-4. 4. Tsien, R.Y., The green fluorescent protein. Annu Rev Biochem, 1998. 67: p. 509-44. 5. Cormack, B.P., R.H. Valdivia, and S. Falkow, FACS-optimized mutants of the green fluorescent protein (GFP). Gene, 1996. 173(1 Spec No): p. 33-8. 6. Zernicka-Goetz, M., et al., An indelible lineage marker for Xenopus using a mutated green fluorescent protein. Development, 1996. 122(12): p. 3719-24. 7. Matz, M.V., K.A. Lukyanov, and S.A. Lukyanov, Family of the green fluorescent protein: journey to the end of the rainbow. Bioessays, 2002. 24(10): p. 953-9. 8. Shaner, N.C., et al., Improved monomeric red, orange and yellow fluorescent proteins derived from Discosoma sp. red fluorescent protein. Nat Biotechnol, 2004. 22(12): p. 1567-72. 9. Muller-Taubenberger, A. and K.I. Anderson, Recent advances using green and red fluorescent protein variants. Appl Microbiol Biotechnol, 2007. 77(1): p. 112. 10. Service, R.F., Nobel Prize in chemistry. Three scientists bask in prize's fluorescent glow. Science, 2008. 322(5900): p. 361. 11. Heintzmann, R. and G. Ficz, Breaking the resolution limit in light microscopy. Methods Cell Biol, 2007. 81: p. 561-80. 12. Heilemann, M., Fluorescence microscopy beyond the diffraction limit. J Biotechnol, 2010. 149(4): p. 243-51. 13. Kerppola, T.K., Visualization of molecular interactions by fluorescence complementation. Nat Rev Mol Cell Biol, 2006. 7(6): p. 449-56. 14. Albertazzi, L., et al., Quantitative FRET analysis with the EGFP-mCherry fluorescent protein pair. Photochem Photobiol, 2009. 85(1): p. 287-97. 103 15. Schwille, P., F.J. Meyer-Almes, and R. Rigler, Dual-color fluorescence crosscorrelation spectroscopy for multicomponent diffusional analysis in solution. Biophys J, 1997. 72(4): p. 1878-86. 16. Mets, Ü. and R. Rigler, Submillisecond detection of single rhodamine molecules in water. Journal of Fluorescence, 1994. 4(3): p. 259-264. 17. Schwille, P., J. Korlach, and W.W. Webb, Fluorescence correlation spectroscopy with single-molecule sensitivity on cell and model membranes. Cytometry, 1999. 36(3): p. 176-82. 18. Weiss, M., H. Hashimoto, and T. Nilsson, Anomalous protein diffusion in living cells as seen by fluorescence correlation spectroscopy. Biophys J, 2003. 84(6): p. 4043-52. 19. Banks, D.S. and C. Fradin, Anomalous diffusion of proteins due to molecular crowding. Biophys J, 2005. 89(5): p. 2960-71. 20. Magde, D., W.W. Webb, and E.L. Elson, Fluorescence correlation spectroscopy. III. Uniform translation and laminar flow. Biopolymers, 1978. 17(2): p. 361-376. 21. Foquet, M., et al., Focal volume confinement by submicrometer-sized fluidic channels. Anal Chem, 2004. 76(6): p. 1618-26. 22. Kinjo, M. and R. Rigler, Ultrasensitive hybridization analysis using fluorescence correlation spectroscopy. Nucleic Acids Research, 1995. 23(10): p. 1795-1799. 23. Schwille, P., F. Oehlenschlager, and N.G. Walter, Quantitative Hybridization Kinetics of DNA Probes to RNA in Solution Followed by Diffusional Fluorescence Correlation Analysis. Biochemistry, 1996. 35(31): p. 1018210193. 24. Auer, M., et al., Fluorescence correlation spectroscopy: lead discovery by miniaturized HTS. Drug Discovery Today, 1998. 3(10): p. 457-465. 25. Pack, C.G., et al., Analysis of interaction between chaperonin GroEL and its substrate using fluorescence correlation spectroscopy. Cytometry, 1999. 36(3): p. 247-53. 26. Wohland, T., et al., Study of ligand-receptor interactions by fluorescence correlation spectroscopy with different fluorophores: evidence that the homopentameric 5-hydroxytryptamine type 3As receptor binds only one ligand. Biochemistry, 1999. 38(27): p. 8671-81. 27. Van Craenenbroeck, E. and Y. Engelborghs, Quantitative characterization of the binding of fluorescently labeled colchicine to tubulin in vitro using fluorescence correlation spectroscopy. Biochemistry, 1999. 38(16): p. 5082-8. 28. Octobre, G., et al., Monitoring the interaction between DNA and a transcription factor (MEF2A) using fluorescence correlation spectroscopy. Comptes Rendus Biologies, 2005. 328(12): p. 1033-1040. 29. Kobayashi, T., et al., Detection of protein-DNA interactions in crude cellular extracts by fluorescence correlation spectroscopy. Analytical Biochemistry, 2004. 332(1): p. 58-66. 104 30. Rauer, B., et al., Fluorescence correlation spectrometry of the interaction kinetics of tetramethylrhodamin alpha-bungarotoxin with Torpedo californica acetylcholine receptor. Biophys Chem, 1996. 58(1-2): p. 3-12. 31. Widengren, J., R. Rigler, and Ü. Mets, Triplet-state monitoring by fluorescence correlation spectroscopy. Journal of Fluorescence, 1994. 4(3): p. 255-258. 32. Widengren, J., U. Mets, and R. Rigler, Fluorescence correlation spectroscopy of triplet states in solution: a theoretical and experimental study. The Journal of Physical Chemistry, 1995. 99(36): p. 13368-13379. 33. Widengren, J., Photodynamic properties of green fluorescent proteins investigated by fluorescence correlation spectroscopy. Chemical Physics, 1999. 250: p. 171-186. 34. Magde, D., E. Elson, and W.W. Webb, Thermodynamic Fluctuations in a Reacting System-Measurement by Fluorescence Correlation Spectroscopy. Phys Rev Lett, 1972. 29(11): p. 705-708. 35. Ehrenberg, M. and R. Rigler, Rotational brownian motion and fluorescence intensify fluctuations. Chemical Physics, 1974. 4(3): p. 390-401. 36. Aragón, S.R. and R. Pecora, Fluorescence correlation spectroscopy and Brownian rotational diffusion. Biopolymers, 1975. 14(1): p. 119-137. 37. Kask, P., et al., Fluorescence correlation spectroscopy in the nanosecond time range: rotational diffusion of bovine carbonic anhydrase B. Eur Biophys J, 1987. 14(4): p. 257-61. 38. Kask, P., et al., Separation of the rotational contribution in fluorescence correlation experiments. Biophys J, 1989. 55(2): p. 213-220. 39. Tsay, J.M., S. Doose, and S. Weiss, Rotational and translational diffusion of peptide-coated CdSe/CdS/ZnS nanorods studied by fluorescence correlation spectroscopy. J Am Chem Soc, 2006. 128(5): p. 1639-47. 40. Loman, A., et al., Measuring rotational diffusion of macromolecules by fluorescence correlation spectroscopy. Photochem Photobiol Sci, 2010. 9(5): p. 627-36. 41. Haupts, U., et al., Dynamics of fluorescence fluctuations in green fluorescent protein observed by fluorescence correlation spectroscopy. Proc Natl Acad Sci U S A, 1998. 95(23): p. 13573-8. 42. Schwille, P., et al., Fluorescence correlation spectroscopy reveals fast optical excitation-driven intramolecular dynamics of yellow fluorescent proteins. Proc Natl Acad Sci U S A, 2000. 97(1): p. 151-6. 43. Malvezzi-Campeggi, F., et al., Light-induced flickering of DsRed provides evidence for distinct and interconvertible fluorescent states. Biophys J, 2001. 81(3): p. 1776-85. 44. Kettling, U., et al., Real-time enzyme kinetics monitored by dual-color fluorescence cross-correlation spectroscopy. Proc Natl Acad Sci U S A, 1998. 95(4): p. 1416-20. 105 45. Saito, K., et al., Direct detection of caspase-3 activation in single live cells by cross-correlation analysis. Biochem Biophys Res Commun, 2004. 324(2): p. 849-54. 46. Kohl, T., E. Haustein, and P. Schwille, Determining Protease Activity In Vivo by Fluorescence Cross-Correlation Analysis. Biophys J, 2005. 89(4): p. 27702782. 47. Rigler, R., et al., Fluorescence cross-correlation: a new concept for polymerase chain reaction. J Biotechnol, 1998. 63(2): p. 97-109. 48. Rippe, K., Simultaneous Binding of Two DNA Duplexes to the NtrC-Enhancer Complex Studied by Two-Color Fluorescence Cross-Correlation Spectroscopy. Biochemistry, 2000. 39(9): p. 2131-2139. 49. Ohrt, T., et al., Fluorescence correlation spectroscopy and fluorescence crosscorrelation spectroscopy reveal the cytoplasmic origination of loaded nuclear RISC in vivo in human cells. Nucleic Acids Res, 2008. 36(20): p. 6439-49. 50. Baudendistel, N., et al., Two-Hybrid Fluorescence Cross-Correlation Spectroscopy Detects Protein-Protein Interactions In Vivo. ChemPhysChem, 2005. 6(5): p. 984-990. 51. Muto, H., et al., Fluorescence Cross-Correlation Analyses of the Molecular Interaction between an Aux/IAA Protein, MSG2/IAA19, and Protein-Protein Interaction Domains of Auxin Response Factors of Arabidopsis Expressed in HeLa Cells. Plant and Cell Physiology, 2006. 47(8): p. 1095-1101. 52. Oyama, R., et al., Protein-protein interaction analysis by C-terminally specific fluorescence labeling and fluorescence cross-correlation spectroscopy. Nucleic Acids Res, 2006. 34(14): p. e102. 53. Maeder, C.I., et al., Spatial regulation of Fus3 MAP kinase activity through a reaction-diffusion mechanism in yeast pheromone signalling. Nat Cell Biol, 2007. 9(11): p. 1319-26. 54. Slaughter, B.D., J.W. Schwartz, and R. Li, Mapping dynamic protein interactions in MAP kinase signaling using live-cell fluorescence fluctuation spectroscopy and imaging. Proc Natl Acad Sci U S A, 2007. 104(51): p. 20320-5. 55. Shi, X., et al., Determination of dissociation constants in living zebrafish embryos with single wavelength fluorescence cross-correlation spectroscopy. Biophys J, 2009. 97(2): p. 678-86. 56. Sudhaharan, T., et al., Determination of in vivo dissociation constant, KD, of Cdc42-effector complexes in live mammalian cells using single wavelength fluorescence cross-correlation spectroscopy. J Biol Chem, 2009. 284(20): p. 13602-9. 57. Liu, P., et al., Investigation of the dimerization of proteins from the epidermal growth factor receptor family by single wavelength fluorescence crosscorrelation spectroscopy. Biophys J, 2007. 93(2): p. 684-98. 58. Neugart, F., et al., Detection of ligand-induced CNTF receptor dimers in living cells by fluorescence cross correlation spectroscopy. Biochim Biophys Acta, 2009. 1788(9): p. 1890-900. 106 59. Hwang, L.C. and T. Wohland, Dual-Color Fluorescence Cross-Correlation Spectroscopy Using Single Laser Wavelength Excitation. ChemPhysChem, 2004. 5(4): p. 549-551. 60. Hwang, L.C. and T. Wohland, Single wavelength excitation fluorescence cross-correlation spectroscopy with spectrally similar fluorophores: Resolution for binding studies. The Journal of Chemical Physics, 2005. 122(11): p. 114708-11. 61. Hwang, L.C., et al., Simultaneous Multicolor Fluorescence Cross-Correlation Spectroscopy to Detect Higher Order Molecular Interactions Using Single Wavelength Laser Excitation. Biophysical Journal, 2006. 91(2): p. 715-727. 62. Rička, J. and T. Binkert, Direct measurement of a distinct correlation function by fluorescence cross correlation. Phys Rev A, 1989. 39(5): p. 2646-2652. 63. Rosales, T., et al., Quantitative detection of the ligand-dependent interaction between the androgen receptor and the co-activator, Tif2, in live cells using two color, two photon fluorescence cross-correlation spectroscopy. Eur Biophys J, 2007. 36(2): p. 153-61. 64. Swift, J.L., et al., Two-photon excitation fluorescence cross-correlation assay for ligand-receptor binding: cell membrane nanopatches containing the human micro-opioid receptor. Anal Chem, 2007. 79(17): p. 6783-91. 65. Ruan, Q. and S.Y. Tetin, Applications of dual-color fluorescence crosscorrelation spectroscopy in antibody binding studies. Anal Biochem, 2008. 374(1): p. 182-95. 66. Nguyen, T.T., et al., Effects of Various Small-Molecule Anesthetics on Vesicle Fusion: A Study Using Two-Photon Fluorescence Cross-Correlation Spectroscopy. J Phys Chem B, 2009. 67. Li, N., et al., Multiple Escherichia coli RecQ Helicase Monomers Cooperate to Unwind Long DNA Substrates: A FLUORESCENCE CROSSCORRELATION SPECTROSCOPY STUDY. J Biol Chem, 2010. 285(10): p. 6922-36. 68. Savatier, J., et al., Estrogen receptor interactions and dynamics monitored in live cells by fluorescence cross-correlation spectroscopy. Biochemistry, 2010. 49(4): p. 772-81. 69. Rigler, R., et al., Fluorescence correlation spectroscopy with high count rate and low background: analysis of translational diffusion. Eur Biophys J 1993. 22(3): p. 169-175. 70. Thews, E., et al., Cross talk free fluorescence cross correlation spectroscopy in live cells. Biophys J, 2005. 89(3): p. 2069-76. 71. Ries, J., et al., Modular scanning FCS quantifies receptor-ligand interactions in living multicellular organisms. Nat Methods, 2009. 6(9): p. 643-5. 72. Brinkmeier, M. and R. Rigler, Flow analysis by means of fluorescence correlation spectroscopy. Experimental Technique of Physics, 1995. 41: p. 205-210. 107 73. Brinkmeier, M., et al., Two-Beam Cross-Correlation: A Method To Characterize Transport Phenomena in Micrometer-Sized Structures. Analytical Chemistry, 1999. 71(3): p. 609-616. 74. Dittrich, P.S. and P. Schwille, Spatial Two-Photon Fluorescence CrossCorrelation Spectroscopy for Controlling Molecular Transport in Microfluidic Structures. Analytical Chemistry, 2002. 74(17): p. 4472-4479. 75. Blom, H., et al., Parallel flow measurements in microstructures by use of a multifocal x diffractive optical fan-out element. Appl Opt, 2002. 41(31): p. 6614-20. 76. Blom, H., et al., Parallel fluorescence detection of single biomolecules in microarrays by a diffractive-optical-designed x fan-out element. Appl Opt, 2002. 41(16): p. 3336-42. 77. Blom, H. and M. Gosch, Parallel confocal detection of single biomolecules using diffractive optics and integrated detector units. Curr Pharm Biotechnol, 2004. 5(2): p. 231-41. 78. Gösch, M., et al., Parallel dual-color fluorescence cross-correlation spectroscopy using diffractive optical elements. J Biomed Opt, 2005. 10(5): p. 054008. 79. Takahashi, Y., et al., Analysis of cellular functions by multipoint fluorescence correlation spectroscopy. Curr Pharm Biotechnol, 2005. 6(2): p. 159-65. 80. Needleman, D.J., Y. Xu, and T.J. Mitchison, Pin-hole array correlation imaging: highly parallel fluorescence correlation spectroscopy. Biophys J, 2009. 96(12): p. 5050-9. 81. Ohsugi, Y. and M. Kinjo, Multipoint fluorescence correlation spectroscopy with total internal reflection fluorescence microscope. J Biomed Opt, 2009. 14(1): p. 014030. 82. Wohland, T., et al., Single Plane Illumination Fluorescence Correlation Spectroscopy (SPIM-FCS) probes inhomogeneous three-dimensional environments. Opt. Express, 2010. 18(10): p. 10627-10641. 83. Kannan, B., et al., Spatially resolved total internal reflection fluorescence correlation microscopy using an electron multiplying charge-coupled device camera. Anal Chem, 2007. 79(12): p. 4463-70. 84. Sankaran, J., et al., Diffusion, transport, and cell membrane organization investigated by imaging fluorescence cross-correlation spectroscopy. Biophys J, 2009. 97(9): p. 2630-9. 85. Petersen, N.O., Scanning fluorescence correlation spectroscopy. I. Theory and simulation of aggregation measurements. Biophys J, 1986. 49(4): p. 809-15. 86. Petersen, N.O., D.C. Johnson, and M.J. Schlesinger, Scanning fluorescence correlation spectroscopy. II. Application to virus glycoprotein aggregation. Biophys J, 1986. 49(4): p. 817-20. 87. Koppel, D.E., et al., Scanning concentration correlation spectroscopy using the confocal laser microscope. Biophys J, 1994. 66(2 Pt 1): p. 502-7. 108 88. Wachsmuth, M., W. Waldeck, and J. Langowski, Anomalous diffusion of fluorescent probes inside living cell nuclei investigated by spatially-resolved fluorescence correlation spectroscopy. J Mol Biol, 2000. 298(4): p. 677-89. 89. Ries, J. and P. Schwille, Studying slow membrane dynamics with continuous wave scanning fluorescence correlation spectroscopy. Biophys J, 2006. 91(5): p. 1915-24. 90. Pan, X., et al., Characterization of flow direction in microchannels and zebrafish blood vessels by scanning fluorescence correlation spectroscopy. J Biomed Opt, 2007. 12(1): p. 014034. 91. Ries, J., et al., Modular scanning FCS quantifies receptor-ligand interactions in living multicellular organisms. Nat Methods, 2009. 92. Berland, K.M., et al., Scanning two-photon fluctuation correlation spectroscopy: particle counting measurements for detection of molecular aggregation. Biophys J, 1996. 71(1): p. 410-20. 93. Ruan, Q., et al., Spatial-temporal studies of membrane dynamics: scanning fluorescence correlation spectroscopy (SFCS). Biophys J, 2004. 87(2): p. 1260-7. 94. Skinner, J.P., Y. Chen, and J.D. Muller, Position-sensitive scanning fluorescence correlation spectroscopy. Biophys J, 2005. 89(2): p. 1288-301. 95. Petrášek, Z., et al., Characterization of protein dynamics in asymmetric cell division by scanning fluorescence correlation spectroscopy. Biophys J, 2008. 95(11): p. 5476-86. 96. Petrášek, Z. and P. Schwille, Precise Measurement of Diffusion Coefficients using Scanning Fluorescence Correlation Spectroscopy. Biophysical Journal, 2008. 94(4): p. 1437-1448. 97. Ries, J. and P. Schwille, New concepts for fluorescence correlation spectroscopy on membranes. Phys Chem Chem Phys, 2008. 10(24): p. 348797. 98. Ries, J., S. Chiantia, and P. Schwille, Accurate determination of membrane dynamics with line-scan FCS. Biophys J, 2009. 96(5): p. 1999-2008. 99. Magatti, D. and F. Ferri, 25 ns software correlator for photon and fluorescence correlation spectroscopy. Review of Scientific Instruments, 2003. 74(2): p. 1135-1144. 100. Wahl, M., et al., Fast calculation of fluorescence correlation data with asynchronous time-correlated single-photon counting. Opt Express, 2003. 11(26): p. 3583-91. 101. Rao, R., et al., Stochastic approach to data analysis in fluorescence correlation spectroscopy. J Phys Chem A, 2006. 110(37): p. 10674-82. 102. Ries, J., et al., A comprehensive framework for fluorescence cross-correlation spectroscopy. New Journal of Physics, 2010. 12(11): p. 113009. 103. Müller, B.K., et al., Pulsed interleaved excitation. Biophys J, 2005. 89(5): p. 3508-22. 109 104. Takahashi, Y., et al., Cross-talk-free fluorescence cross-correlation spectroscopy by the switching method. Cell Struct Funct, 2008. 33(1): p. 14350. 105. Miller, A.E., et al., Fluorescence cross-correlation spectroscopy as a universal method for protein detection with low false positives. Anal Chem, 2009. 81(14): p. 5614-22. 106. Böhmer, M., et al., Time-resolved fluorescence correlation spectroscopy. Chemical Physics Letters, 2002. 353(5-6): p. 439-445. 107. Benda, A., et al., Fluorescence lifetime correlation spectroscopy combined with lifetime tuning: new perspectives in supported phospholipid bilayer research. Langmuir, 2006. 22(23): p. 9580-5. 108. Kapusta, P., et al., Fluorescence lifetime correlation spectroscopy. J Fluoresc, 2007. 17(1): p. 43-8. 109. Yang, F., L.G. Moss, and G.N. Phillips, The molecular structure of green fluorescent protein. Nat Biotech, 1996. 14(10): p. 1246-1251. 110. Zacharias, D.A., et al., Partitioning of lipid-modified monomeric GFPs into membrane microdomains of live cells. Science, 2002. 296(5569): p. 913-6. 111. Malengo, G., et al., Fluorescence correlation spectroscopy and photon counting histogram on membrane proteins: functional dynamics of the glycosylphosphatidylinositol-anchored urokinase plasminogen activator receptor. J Biomed Opt, 2008. 13(3): p. 031215. 112. Huet, S., et al., Nuclear import and assembly of influenza A virus RNA polymerase studied in live cells by fluorescence cross-correlation spectroscopy. J Virol, 2010. 84(3): p. 1254-64. 113. Park, H., et al., In vivo quantitative analysis of PKA subunit interaction and cAMP level by dual color fluorescence cross correlation spectroscopy. Mol Cells, 2008. 26(1): p. 87-92. 114. Lillemeier, B.F., et al., TCR and Lat are expressed on separate protein islands on T cell membranes and concatenate during activation. Nat Immunol, 2010. 11(1): p. 90-6. 115. Campbell, R.E., et al., A monomeric red fluorescent protein. Proc Natl Acad Sci U S A, 2002. 99(12): p. 7877-82. 116. Baird, G.S., D.A. Zacharias, and R.Y. Tsien, Biochemistry, mutagenesis, and oligomerization of DsRed, a red fluorescent protein from coral. Proc Natl Acad Sci U S A, 2000. 97(22): p. 11984-9. 117. Gross, L.A., et al., The structure of the chromophore within DsRed, a red fluorescent protein from coral. Proc Natl Acad Sci U S A, 2000. 97(22): p. 11990-5. 118. Hillesheim, L.N., Y. Chen, and J.D. Muller, Dual-Color Photon Counting Histogram Analysis of mRFP1 and EGFP in Living Cells. Biophys J, 2006. 91(11): p. 4273-4284. 110 119. Hendrix, J., et al., Dark states in monomeric red fluorescent proteins studied by fluorescence correlation and single molecule spectroscopy. Biophys J, 2008. 94(10): p. 4103-13. 120. Kogure, T., et al., A fluorescent variant of a protein from the stony coral Montipora facilitates dual-color single-laser fluorescence cross-correlation spectroscopy. Nat Biotechnol, 2006. 24(5): p. 577-81. 121. Elson, E.L. and D. Magde, Fluorescence correlation spectroscopy. I. Conceptual basis and theory. Biopolymers, 1974. 13(1): p. 1-27. 122. Magde, D., E.L. Elson, and W.W. Webb, Fluorescence correlation spectroscopy. II. An experimental realization. Biopolymers, 1974. 13(1): p. 29-61. 123. Koppel, D.E., Statistical accuracy in fluorescence correlation spectroscopy. Phys Rev A, 1974. 10(6): p. 1938-1945. 124. Thompson, N.L., Fluorescence correlation spectroscopy, in Topics in Fluorescence Spectroscopy, J.R. Lakowicz, Editor. 1991, Plenum Press: New York. p. 337-378. 125. Shi, X. and T. Wohland, Fluorescence correlation spectroscopy, in Nanoscopy and Multidimensional Optical Fluorescence Microscopy, A. Diaspro, Editor. 2009, Taylor & Francis: Boca Raton. 126. Aragon, S.R. and R. Pecora, Fluorescence correlation spectroscopy as a probe of molecular dynamics. J Chem Phys, 1976. 64: p. 1791. 127. Wu, J. and K.M. Berland, Propagators and time-dependent diffusion coefficients for anomalous diffusion. Biophys J, 2008. 95(4): p. 2049-52. 128. Meseth, U., et al., Resolution of fluorescence correlation measurements. Biophys J, 1999. 76(3): p. 1619-31. 129. Ruttinger, S., et al., Comparison and accuracy of methods to determine the confocal volume for quantitative fluorescence correlation spectroscopy. J Microsc, 2008. 232(2): p. 343-352. 130. Widengren, J. and R. Rigler, Fluorescence correlation spectroscopy as a tool to investigate chemical reactions in solutions and on cell surfaces. Cell Mol Biol (Noisy-le-grand), 1998. 44(5): p. 857-79. 131. Bonnet, G., O. Krichevsky, and A. Libchaber, Kinetics of conformational fluctuations in DNA hairpin-loops. Proc Natl Acad Sci U S A, 1998. 95(15): p. 8602-6. 132. Widengren, J., et al., Two New Concepts to Measure Fluorescence Resonance Energy Transfer via Fluorescence Correlation Spectroscopy: Theory and Experimental Realizations. The Journal of Physical Chemistry A, 2001. 105(28): p. 6851-6866. 133. Lamb, D.C., et al., Sensitivity enhancement in fluorescence correlation spectroscopy of multiple species using time-gated detection. Biophys J, 2000. 79(2): p. 1129-38. 111 134. Mütze, J., T. Ohrt, and P. Schwille (2009) Fluorescence correlation spectroscopy in vivo. Laser & Photonics Reviews, NA DOI: 10.1002/lpor.200910041. 135. Pan, X., et al., Multifunctional fluorescence correlation microscope for intracellular and microfluidic measurements. Rev Sci Instrum, 2007. 78(5): p. 053711. 136. Rarbach, M., et al., Dual-color fluorescence cross-correlation spectroscopy for monitoring the kinetics of enzyme-catalyzed reactions. Methods, 2001. 24(2): p. 104-16. 137. Etienne-Manneville, S. and A. Hall, Rho GTPases in cell biology. Nature, 2002. 420(6916): p. 629-635. 138. Bishop, A.L. and A. Hall, Rho GTPases and their effector proteins. Biochem J, 2000. 348 Pt 2: p. 241-55. 139. Hart, M.J., et al., IQGAP1, a calmodulin-binding protein with a rasGAPrelated domain, is a potential effector for cdc42Hs. EMBO J, 1996. 15(12): p. 2997-3005. 140. Kuroda, S., et al., Identification of IQGAP as a putative target for the small GTPases, Cdc42 and Rac1. J Biol Chem, 1996. 271(38): p. 23363-7. 141. Watanabe, T., et al., Interaction with IQGAP1 links APC to Rac1, Cdc42, and actin filaments during cell polarization and migration. Dev Cell, 2004. 7(6): p. 871-83. 142. Brandt, D.T. and R. Grosse, Get to grips: steering local actin dynamics with IQGAPs. EMBO Rep, 2007. 8(11): p. 1019-23. 143. Limpert, E., W.A. Stahel, and M. Abbt, Log-normal distributions across the sciences: Keys and clues. Bioscience, 2001. 51(5): p. 341-352. 144. Erickson, J.W., R.A. Cerione, and M.J. Hart, Identification of an Actin Cytoskeletal Complex That Includes IQGAP and the Cdc42 GTPase. Journal of Biological Chemistry, 1997. 272(39): p. 24443-24447. 145. Coso, O.A., et al., The small GTP-binding proteins Rac1 and Cdc42 regulate the activity of the JNK/SAPK signaling pathway. Cell, 1995. 81(7): p. 113746. 146. Feig, L.A. and G.M. Cooper, Inhibition of NIH 3T3 cell proliferation by a mutant ras protein with preferential affinity for GDP. Mol Cell Biol, 1988. 8(8): p. 3235-43. 147. Rossman, K.L., C.J. Der, and J. Sondek, GEF means go: turning on RHO GTPases with guanine nucleotide-exchange factors. Nat Rev Mol Cell Biol, 2005. 6(2): p. 167-80. 148. Ho, Y.D., et al., IQGAP1 integrates Ca2+/calmodulin and Cdc42 signaling. J Biol Chem, 1999. 274(1): p. 464-70. 149. Pampaloni, F., E.G. Reynaud, and E.H. Stelzer, The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol, 2007. 8(10): p. 839-45. 112 150. Maroun, M. and A. Aronheim, A novel in vivo assay for the analysis of protein-protein interaction. Nucleic Acids Res, 1999. 27(13): p. e4. 151. Knauer, S.K., et al., Translocation biosensors to study signal-specific nucleocytoplasmic transport, protease activity and protein-protein interactions. Traffic, 2005. 6(7): p. 594-606. 152. Knauer, S.K. and R.H. Stauber, Development of an autofluorescent translocation biosensor system to investigate protein-protein interactions in living cells. Anal Chem, 2005. 77(15): p. 4815-20. 153. Heydorn, A., et al., Protein translocation assays: key tools for accessing new biological information with high-throughput microscopy. Methods Enzymol, 2006. 414: p. 513-30. 154. Piljic, A. and C. Schultz, Analysis of protein complex hierarchy in living cells. ACS Chem Biol, 2008. 3(12): p. 749-55. 155. Piljic, A. and C. Schultz, Annexin A4 self-association modulates general membrane protein mobility in living cells. Mol Biol Cell, 2006. 17(7): p. 331828. 156. Prives, C. and V. Gottifredi, The p21 and PCNA partnership: a new twist for an old plot. Cell Cycle, 2008. 7(24): p. 3840-6. 157. Heinze, K.G., M. Jahnz, and P. Schwille, Triple-color coincidence analysis: one step further in following higher order molecular complex formation. Biophys J, 2004. 86(1 Pt 1): p. 506-16. 158. Weidemann, T., et al., Analysis of ligand binding by two-colour fluorescence cross-correlation spectroscopy. Single Molecules, 2002. 3(1): p. 49-61. 159. Kohl, T., et al., A protease assay for two-photon crosscorrelation and FRET analysis based solely on fluorescent proteins. Proc Natl Acad Sci U S A, 2002. 99(19): p. 12161-6. 160. Kapanidis, A.N., et al., Fluorescence-aided molecule sorting: analysis of structure and interactions by alternating-laser excitation of single molecules. Proc Natl Acad Sci U S A, 2004. 101(24): p. 8936-41. 161. Chen, Y., et al., Molecular brightness characterization of EGFP in vivo by fluorescence fluctuation spectroscopy. Biophys J, 2002. 82(1 Pt 1): p. 133-44. 162. Slaughter, B.D., et al., SAM domain-based protein oligomerization observed by live-cell fluorescence fluctuation spectroscopy. PLoS ONE, 2008. 3(4): p. e1931. 163. Owen, D., et al., The IQGAP1-Rac1 and IQGAP1-Cdc42 interactions: interfaces differ between the complexes. J Biol Chem, 2008. 283(3): p. 1692704. 164. Sokol, S.Y., Z. Li, and D.B. Sacks, The effect of IQGAP1 on Xenopus embryonic ectoderm requires Cdc42. J Biol Chem, 2001. 276(51): p. 4842530. 165. Nevins, A.K. and D.C. Thurmond, A direct interaction between Cdc42 and vesicle-associated membrane protein regulates SNARE-dependent insulin exocytosis. J Biol Chem, 2005. 280(3): p. 1944-52. 113 166. Kastrup, L., et al., Fluorescence fluctuation spectroscopy in subdiffraction focal volumes. Phys Rev Lett, 2005. 94(17): p. 178104. 167. Vobornik, D., et al., Fluorescence correlation spectroscopy with subdiffraction-limited resolution using near-field optical probes. Applied Physics Letters, 2008. 93(16): p. 163904-3. 168. Wenger, J., et al., Single molecule fluorescence in rectangular nano-apertures. Opt Express, 2005. 13(18): p. 7035-44. 169. Ries, J., et al., Supercritical angle fluorescence correlation spectroscopy. Biophys J, 2008. 94(1): p. 221-9. 170. Chen, J. and J. Irudayaraj, Fluorescence lifetime cross correlation spectroscopy resolves EGFR and antagonist interaction in live cells. Anal Chem, 2010. 82(15): p. 6415-21. 171. Garai, K., M. Muralidhar, and S. Maiti, Fiber-optic fluorescence correlation spectrometer. Appl Opt, 2006. 45(28): p. 7538-42. 172. Garai, K., R. Sureka, and S. Maiti, Detecting amyloid-beta aggregation with fiber-based fluorescence correlation spectroscopy. Biophys J, 2007. 92(7): p. L55-7. 173. Chang, Y.C., et al., Two-photon fluorescence correlation spectroscopy through a dual-clad optical fiber. Opt Express, 2008. 16(17): p. 12640-9. 174. Aouani, H., et al., Optical-fiber-microsphere for remote fluorescence correlation spectroscopy. Opt. Express, 2009. 17(21): p. 19085-19092. 175. Reynaud, E.G., et al., Light sheet-based fluorescence microscopy: more dimensions, more photons, and less photodamage. HFSP J, 2008. 2(5): p. 26675. 176. Digman, M.A., et al., Measuring fast dynamics in solutions and cells with a laser scanning microscope. Biophys J, 2005. 89(2): p. 1317-27. 177. Digman, M.A., et al., Fluctuation correlation spectroscopy with a laserscanning microscope: exploiting the hidden time structure. Biophys J, 2005. 88(5): p. L33-6. 178. Padilla-Parra, S., et al., Quantitative comparison of different fluorescent protein couples for fast FRET-FLIM acquisition. Biophys J, 2009. 97(8): p. 2368-76. 179. Chen, Y., L.N. Wei, and J.D. Muller, Probing protein oligomerization in living cells with fluorescence fluctuation spectroscopy. Proc Natl Acad Sci U S A, 2003. 100(26): p. 15492-7. 180. Shaner, N.C., G.H. Patterson, and M.W. Davidson, Advances in fluorescent protein technology. J Cell Sci, 2007. 120(Pt 24): p. 4247-60. 181. Nienhaus, G.U. and J. Wiedenmann, Structure, dynamics and optical properties of fluorescent proteins: perspectives for marker development. Chemphyschem, 2009. 10(9-10): p. 1369-79. 114 [...]... 1 In summary, FCCS is still in the stages of development In vivo application and interpretation of the data still require attention and improvement Therefore the aim of this thesis is the application and development of FCCS to quantitate protein-protein interactions in vivo The thesis contains six chapters and is structured into the following sections: Chapter 2 introduces the basic principles and instrumentation... co-immunoprecipitation involves lysing the cell before using anti-bodies to pull down the target protein complexes Another technique, the yeast-two-hybrid system detects protein-protein 2 Chapter 1 interactions in vivo but it requires the proteins to be expressed in yeast which is not the native environment for the protein of interest (unless it is a yeast protein) Therefore there is a need to monitor protein-protein interactions. .. strength of interaction In special cases such as the combination of fluorescence lifetime imaging microscopy to FRET (FLIM-FRET), one can determine the amount of donor molecules in complex which gives an estimate of the binding strength [14] Binding strength is typically represented by dissociation constant Kd A technique which allows the determination of Kd is fluorescence cross-correlation spectroscopy. .. role in a cell system As a cell functions through a network of protein-protein interactions, it is vital to study these interactions as it allows one to understand the role of a particular protein and its place in the whole network Many techniques, which are mainly biochemical in nature, are available to detected protein-protein interactions However, they are either in vitro methods or qualitative in. .. FCCS investigates the synchronized fluorescence fluctuations of two different fluorophores in order to detect biomolecular interactions When the movements of two molecules are synchronized, they are most likely to be interacting FCCS is an extension of fluorescence correlation spectroscopy (FCS) The basic principles of FCS is based on extracting statistical information that is embedded within the fluorescence. .. imaging and spectroscopy are important techniques in the area of modern biology Today, fluorescent tagging of biomolecules allows researchers to monitor even single molecules of interest in organisms This advance has been possible because of the advent of green fluorescence protein (GFP), which allowed genetic labeling of proteins within cell cultures or in vivo in a selective and specific manner GFP was... interactions using non-invasive methods in the native cell environment and this is where the optical imaging and spectroscopy tools fill the gap Fluorescence microscopy is most commonly used to monitor the expression of proteins in cells Due to its diffraction limited resolution of ~250 nm, it is not possible to detect protein-protein interactions even if two proteins are localized in the same pixel of an image... Shimomura, Martin Chalfie and Roger Y Tsien for the discovery and development of GFP [10] The advent of GFP leads to the development and applications of many optical imaging and spectroscopy tools in biology These tools have been helpful in discovering molecular interactions, molecular dynamics and localization of molecules Among these many different processes in a cell, protein-protein interactions. .. affect FCCS studies in vivo but is usually overlooked These issues include mismatch in effective volumes, nonfluorescent fluorescent labels, FRET, photobleaching and endogenous proteins All 9 Chapter 1 these factors influence the quality of the determined Kd Major findings include quantitating the fraction of non-fluorescent RFPs (mRFP and mCherry) and investigating the relationship of Kd with non-fluorescent... fitting algorithms [101] Despite the technological advancements, performing single molecule sensitive measurements such as FCS/FCCS in vivo is a challenge The background autofluorescence of other molecules in a cell sometimes interfere with the measurement On top of this, the commonly used GFP mutants are low in brightness and less photostable when compared to organic dyes resulting in less photons being . processes in a cell, protein-protein interactions play an important role in a cell system. As a cell functions through a network of protein-protein interactions, it is vital to study these interactions. variant of FCCS, to study protein-protein interactions in vivo. The thesis is organized into the following chapters: Chapter 1 starts with discussing the importance of green florescent proteins. STUDY OF BIOMOLECULAR INTERACTIONS IN VIVO BY MULTICOLOUR FLUORESCENCE SPECTROSCOPY FOO YONG HWEE (B.Sc.(Hons.), NUS) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

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