Fluorescence fluctuation spectroscopy (FFS) techniques provide information at the single-molecule level with excellent time resolution. Usually applied at a single spot in a sample, they have been recently extended into imaging formats, referred to as imaging FFS. They provide spatial information at the optical diffraction limit and temporal information in the microsecond to millisecond range. This review provides an overview of the different modalities in which imaging FFS techniques have been implemented and discusses present imaging FFS capabilities and limitations. A combination of imaging FFS and nanoscopy would allow one to record information with the detailed spatial information of nanoscopy, which is ∼20 nm and limited only by fluorophore size and labeling density, and the time resolution of imaging FFS, limited by the fluorescence lifetime. This combination would provide new insights into biological events by providing spatiotemporal resolution at unprecedented levels.


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Literature Cited

  1. Buonomano DV. 1.  2007. The biology of time across different scales. Nat. Chem. Biol. 3:594–97 [Google Scholar]
  2. Secrier M, Schneider R. 2.  2013. Visualizing time-related data in biology, a review. Brief. Bioinforma. In press [Google Scholar]
  3. Garini Y, Vermolen BJ, Young IT. 3.  2005. From micro to nano: recent advances in high-resolution microscopy. Curr. Opin. Biotechnol. 16:3–12 [Google Scholar]
  4. Schermelleh L, Heintzmann R, Leonhardt H. 4.  2010. A guide to super-resolution fluorescence microscopy. J. Cell Biol. 190:165–75 [Google Scholar]
  5. Fischer RS, Wu Y, Kanchanawong P, Shroff H, Waterman CM. 5.  2011. Microscopy in 3D: a biologist's toolbox. Trends Cell Biol. 21:682–91 [Google Scholar]
  6. Huang B, Bates M, Zhuang X. 6.  2009. Super-resolution fluorescence microscopy. Annu. Rev. Biochem. 78:993–1016 [Google Scholar]
  7. Huang B, Babcock H, Zhuang X. 7.  2010. Breaking the diffraction barrier: super-resolution imaging of cells. Cell 143:1047–58 [Google Scholar]
  8. Kanchanawong P, Waterman CM. 8.  2012. Advances in light-based imaging of three-dimensional cellular ultrastructure. Curr. Opin. Cell Biol. 24:125–33 [Google Scholar]
  9. Chao J, Ram S, Ward ES, Ober RJ. 9.  2013. Ultrahigh accuracy imaging modality for super-localization microscopy. Nat. Methods 10:335–38 [Google Scholar]
  10. Fernández-Suárez M, Ting AY. 10.  2008. Fluorescent probes for super-resolution imaging in living cells. Nat. Rev. Mol. Cell Biol. 9:929–43 [Google Scholar]
  11. York AG, Parekh SH, Dalle Nogare D, Fischer RS, Temprine K. 11.  et al. 2012. Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy. Nat. Methods 9:749–54 [Google Scholar]
  12. Huang F, Hartwich TMP, Rivera-Molina FE, Lin Y, Duim WC. 12.  et al. 2013. Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms. Nat. Methods 10:653–58 [Google Scholar]
  13. Buchholz J, Krieger JW, Mocsar G, Kreith B, Charbon E. 13.  et al. 2012. FPGA implementation of a 32×32 autocorrelator array for analysis of fast image series. Opt. Express 20:17767–82 [Google Scholar]
  14. Miyawaki A. 14.  2011. Proteins on the move: insights gained from fluorescent protein technologies. Nat. Rev. Mol. Cell Biol. 12:656–68 [Google Scholar]
  15. Progatzky F, Dallman MJ, Lo Celso C. 15.  2013. From seeing to believing: labelling strategies for in vivo cell-tracking experiments. Interface Focus 3:20130001 [Google Scholar]
  16. Axelrod D, Omann GM. 16.  2006. Combinatorial microscopy. Nat. Rev. Mol. Cell Biol. 7:944–52 [Google Scholar]
  17. Singh AP, Krieger JW, Buchholz J, Charbon E, Langowski J, Wohland T. 17.  2013. The performance of 2D array detectors for light sheet based fluorescence correlation spectroscopy. Opt. Express 21:8652–68 [Google Scholar]
  18. Krichevsky O, Bonnet G. 18.  2002. Fluorescence correlation spectroscopy: the technique and its applications. Rep. Prog. Phys. 65:251–97 [Google Scholar]
  19. Petrášek Z, Schwille P. 19.  2009. Fluctuations as a source of information in fluorescence microscopy. J. R. Soc. Interface 6:S15–25 [Google Scholar]
  20. Mütze J, Ohrt T, Petrášek Z, Schwille P. 20.  2010. In vivo fluorescence correlation and cross-correlation spectroscopy. Single Molecule Spectroscopy in Chemistry, Physics and Biology A Gräslund, R Rigler, J Widengren 139–54 New York: Springer [Google Scholar]
  21. Digman MA, Gratton E. 21.  2011. Lessons in fluctuation correlation spectroscopy. Annu. Rev. Phys. Chem. 62:645–68 [Google Scholar]
  22. Ries J, Weidemann T, Schwille P. 22.  2012. Fluorescence correlation spectroscopy. Compr. Biophys. 2:210–45 [Google Scholar]
  23. Haustein E, Schwille P. 23.  2007. Fluorescence correlation spectroscopy: novel variations of an established technique. Annu. Rev. Biophys. Biomol. Struct. 36:151–69 [Google Scholar]
  24. Kolin DL, Wiseman PW. 24.  2007. Advances in image correlation spectroscopy: measuring number densities, aggregation states, and dynamics of fluorescently labeled macromolecules in cells. Cell Biochem. Biophys. 49:141–64 [Google Scholar]
  25. Wiseman PW. 25.  2012. Image correlation spectroscopy. Compr. Biophys. 2:246–59 [Google Scholar]
  26. Wiseman PW. 26.  2013. Image correlation spectroscopy: mapping correlations in space, time, and reciprocal space. Methods Enzymol. 518:245–67 [Google Scholar]
  27. MacDonald DKC. 27.  1962. Noise and Fluctuations: An Introduction New York: Wiley118 [Google Scholar]
  28. Magde D, Elson E, Webb W. 28.  1972. Thermodynamic fluctuations in a reacting system—measurement by fluorescence correlation spectroscopy. Phys. Rev. Lett. 29:705–8 [Google Scholar]
  29. Elson EL, Magde D. 29.  1974. Fluorescence correlation spectroscopy. I. Conceptual basis and theory. Biopolymers 13:1–27 [Google Scholar]
  30. Magde D, Elson EL. 30.  1974. Fluorescence correlation spectroscopy. II. An experimental realization. Biopolymers 13:29–41 [Google Scholar]
  31. Petrov EP, Schwille P. 31.  2008. State of the art and novel trends in fluorescence correlation spectroscopy. Standardization and Quality Assurance in Fluorescence Measurements II U Resch-Genger 145–97 New York: Springer [Google Scholar]
  32. Ries J, Petrášek Z, García-Sáez AJ, Schwille P. 32.  2010. A comprehensive framework for fluorescence cross-correlation spectroscopy. New J. Phys. 12:113009 [Google Scholar]
  33. Hess ST, Huang S, Heikal AA, Webb WW. 33.  2002. Biological and chemical applications of fluorescence correlation spectroscopy: a review. Biochemistry 41:697–705 [Google Scholar]
  34. Chen H, Farkas ER, Webb WW. 34.  2008. In vivo applications of fluorescence correlation spectroscopy. Methods Cell Biol. 89:3–35 [Google Scholar]
  35. Qian H, Elson EL. 35.  1990. On the analysis of high order moments of fluorescence fluctuations. Biophys. J. 57:375–80 [Google Scholar]
  36. Qian H, Elson EL. 36.  1990. Distribution of molecular aggregation by analysis of fluctuation moments. Proc. Natl. Acad. Sci. USA 87:5479–83 [Google Scholar]
  37. Meseth U, Wohland T, Rigler R, Vogel H. 37.  1999. Resolution of fluorescence correlation measurements. Biophys. J. 76:1619–31 [Google Scholar]
  38. Yu L, Tan M, Ho B, Ding JL, Wohland T. 38.  2006. Determination of critical micelle concentrations and aggregation numbers by fluorescence correlation spectroscopy: aggregation of a lipopolysaccharide. Anal. Chim. Acta 556:216–25 [Google Scholar]
  39. Chen Y, Müller JD, So PTC, Gratton E. 39.  1999. The photon counting histogram in fluorescence fluctuation spectroscopy. Biophys. J. 77:553–67 [Google Scholar]
  40. Müller JD, Chen Y, Gratton E. 40.  2000. Resolving heterogeneity on the single molecular level with the photon-counting histogram. Biophys. J. 78:474–86 [Google Scholar]
  41. Kask P, Palo K, Ullmann D, Gall K. 41.  1999. Fluorescence-intensity distribution analysis and its application in biomolecular detection technology. Proc. Natl. Acad. Sci. USA 96:13756–61 [Google Scholar]
  42. Kask P, Palo K, Fay N, Brand L, Mets U. 42.  et al. 2000. Two-dimensional fluorescence intensity distribution analysis: theory and applications. Biophys. J. 78:1703–13 [Google Scholar]
  43. Perroud TD, Bokoch MP, Zare RN. 43.  2005. Cytochrome c conformations resolved by the photon counting histogram: watching the alkaline transition with single-molecule sensitivity. Proc. Natl. Acad. Sci. USA 102:17570–75 [Google Scholar]
  44. Rudiger M, Haupts U, Moore KJ, Pope AJ. 44.  2001. Single-molecule detection technologies in miniaturized high throughput screening: binding assays for G protein–coupled receptors using fluorescence intensity distribution analysis and fluorescence anisotropy. J. Biomol. Screen. 6:29–37 [Google Scholar]
  45. Herrick-Davis K, Grinde E, Lindsley T, Cowan A, Mazurkiewicz JE. 45.  2012. Oligomer size of the serotonin 5-hydroxytryptamine 2C (5-HT2C) receptor revealed by fluorescence correlation spectroscopy with photon counting histogram analysis: evidence for homodimers without monomers or tetramers. J. Biol. Chem. 287:23604–14 [Google Scholar]
  46. Song Q, Pallikkuth S, Bossuyt J, Bers DM, Robia SL. 46.  2011. Phosphomimetic mutations enhance oligomerization of phospholemman and modulate its interaction with the Na/K-ATPase. J. Biol. Chem. 286:9120–26 [Google Scholar]
  47. Saffarian S, Li Y, Elson EL, Pike LJ. 47.  2007. Oligomerization of the EGF receptor investigated by live cell fluorescence intensity distribution analysis. Biophys. J. 93:1021–31 [Google Scholar]
  48. Müller JD. 48.  2004. Cumulant analysis in fluorescence fluctuation spectroscopy. Biophys. J. 86:3981–92 [Google Scholar]
  49. Perroud TD, Huang B, Zare RN. 49.  2005. Effect of bin time on the photon counting histogram for one-photon excitation. Chemphyschem 6:905–12 [Google Scholar]
  50. Palo K, Mets U, Jager S, Kask P, Gall K. 50.  2000. Fluorescence intensity multiple distributions analysis: concurrent determination of diffusion times and molecular brightness. Biophys. J. 79:2858–66 [Google Scholar]
  51. Wu B, Müller JD. 51.  2005. Time-integrated fluorescence cumulant analysis in fluorescence fluctuation spectroscopy. Biophys. J. 89:2721–35 [Google Scholar]
  52. Wu B, Singer RH, Müller JD. 52.  2013. Time-integrated fluorescence cumulant analysis and its application in living cells. Methods Enzymol. 518:99–119 [Google Scholar]
  53. Palo K, Brand L, Eggeling C, Jager S, Kask P, Gall K. 53.  2002. Fluorescence intensity and lifetime distribution analysis: toward higher accuracy in fluorescence fluctuation spectroscopy. Biophys. J. 83:605–18 [Google Scholar]
  54. Laurence TA, Kapanidis AN, Kong XX, Chemla DS, Weiss S. 54.  2004. Photon arrival-time interval distribution (PAID): a novel tool for analyzing molecular interactions. J. Phys. Chem. B 108:3051–67 [Google Scholar]
  55. Digman MA, Dalal R, Horwitz AF, Gratton E. 55.  2008. Mapping the number of molecules and brightness in the laser scanning microscope. Biophys. J. 94:2320–32 [Google Scholar]
  56. Unruh JR, Gratton E. 56.  2008. Analysis of molecular concentration and brightness from fluorescence fluctuation data with an electron multiplied CCD camera. Biophys. J. 95:5385–98 [Google Scholar]
  57. Wu B, Chen Y, Müller JD. 57.  2009. Fluorescence fluctuation spectroscopy of mCherry in living cells. Biophys. J. 96:2391–404 [Google Scholar]
  58. Adu-Gyamfi E, Digman MA, Gratton E, Stahelin RV. 58.  2012. Investigation of Ebola VP40 assembly and oligomerization in live cells using number and brightness analysis. Biophys. J. 102:2517–25 [Google Scholar]
  59. James NG, Digman MA, Gratton E, Barylko B, Ding X. 59.  et al. 2012. Number and brightness analysis of LRRK2 oligomerization in live cells. Biophys. J. 102:L41–43 [Google Scholar]
  60. Hellriegel C, Caiolfa VR, Corti V, Sidenius N, Zamai M. 60.  2011. Number and brightness image analysis reveals ATF-induced dimerization kinetics of uPAR in the cell membrane. FASEB J. 25:2883–97 [Google Scholar]
  61. Wu J, Corbett AH, Berland KM. 61.  2009. The intracellular mobility of nuclear import receptors and NLS cargoes. Biophys. J. 96:3840–49 [Google Scholar]
  62. Ross JA, Chen Y, Müller J, Barylko B, Wang L. 62.  et al. 2011. Dimeric endophilin A2 stimulates assembly and GTPase activity of dynamin 2. Biophys. J. 100:729–37 [Google Scholar]
  63. Digman MA, Wiseman PW, Choi C, Horwitz AR, Gratton E. 63.  2009. Stoichiometry of molecular complexes at adhesions in living cells. Proc. Natl. Acad. Sci. USA 106:2170–75Determines the existence and stoichiometry of the biomolecular complexes in different organelles by cc-N&B. [Google Scholar]
  64. Petersen NO. 64.  1986. Scanning fluorescence correlation spectroscopy. I. Theory and simulation of aggregation measurements. Biophys. J. 49:809–15 [Google Scholar]
  65. Petersen NO, Johnson DC, Schlesinger MJ. 65.  1986. Scanning fluorescence correlation spectroscopy. II. Application to virus glycoprotein aggregation. Biophys. J. 49:817–20 [Google Scholar]
  66. Ries J, Yu SR, Burkhardt M, Brand M, Schwille P. 66.  2009. Modular scanning FCS quantifies receptor-ligand interactions in living multicellular organisms. Nat. Methods 6:643–45 [Google Scholar]
  67. Petrášek Z, Hoege C, Mashaghi A, Ohrt T, Hyman AA, Schwille P. 67.  2008. Characterization of protein dynamics in asymmetric cell division by scanning fluorescence correlation spectroscopy. Biophys. J. 95:5476–86 [Google Scholar]
  68. Ries J, Schwille P. 68.  2006. Studying slow membrane dynamics with continuous wave scanning fluorescence correlation spectroscopy. Biophys. J. 91:1915–24 [Google Scholar]
  69. Ries J, Chiantia S, Schwille P. 69.  2009. Accurate determination of membrane dynamics with line-scan FCS. Biophys. J. 96:1999–2008 [Google Scholar]
  70. Ries J, Schwille P. 70.  2008. New concepts for fluorescence correlation spectroscopy on membranes. Phys. Chem. Chem. Phys. 10:3487–97 [Google Scholar]
  71. Petrášek Z, Ries J, Schwille P. 71.  2010. Scanning FCS for the characterization of protein dynamics in live cells. Methods Enzymol. 472:317–43 [Google Scholar]
  72. Digman MA, Sengupta P, Wiseman PW, Brown CM, Horwitz AR, Gratton E. 72.  2005. Fluctuation correlation spectroscopy with a laser-scanning microscope: exploiting the hidden time structure. Biophys. J. 88:L33–36 [Google Scholar]
  73. Digman MA, Gratton E. 73.  2012. Scanning image correlation spectroscopy. BioEssays 34377–85 [Google Scholar]
  74. Digman MA, Stakic M, Gratton E. 74.  2013. Raster image correlation spectroscopy and number and brightness analysis. Methods Enzymol. 518:121–44 [Google Scholar]
  75. Sanabria H, Digman MA, Gratton E, Waxham MN. 75.  2008. Spatial diffusivity and availability of intracellular calmodulin. Biophys. J. 95:6002–15 [Google Scholar]
  76. Gielen E, Smisdom N, vandeVen M, De Clercq B, Gratton E. 76.  et al. 2009. Measuring diffusion of lipid-like probes in artificial and natural membranes by raster image correlation spectroscopy (RICS): use of a commercial laser-scanning microscope with analog detection. Langmuir 25:5209–18 [Google Scholar]
  77. Groner N, Capoulade J, Cremer C, Wachsmuth M. 77.  2010. Measuring and imaging diffusion with multiple scan speed image correlation spectroscopy. Opt. Express 18:21225–37 [Google Scholar]
  78. Digman MA, Wiseman PW, Horwitz AR, Gratton E. 78.  2009. Detecting protein complexes in living cells from laser scanning confocal image sequences by the cross correlation raster image spectroscopy method. Biophys. J. 96:707–16Studies the sites of binding-unbinding dynamics of the biomolecular complexes in live cells. [Google Scholar]
  79. Norris SC, Humpolickova J, Amler E, Huranova M, Buzgo M. 79.  et al. 2011. Raster image correlation spectroscopy as a novel tool to study interactions of macromolecules with nanofiber scaffolds. Acta Biomater. 7:4195–203 [Google Scholar]
  80. Petersen NO, Hoddelius PL, Wiseman PW, Seger O, Magnusson KE. 80.  1993. Quantitation of membrane receptor distributions by image correlation spectroscopy: concept and application. Biophys. J. 65:1135–46 [Google Scholar]
  81. Zhang B, Zerubia J, Olivo-Marin JC. 81.  2007. Gaussian approximations of fluorescence microscope point-spread function models. Appl. Opt. 46:1819–29 [Google Scholar]
  82. Keating E, Nohe A, Petersen NO. 82.  2008. Studies of distribution, location and dynamic properties of EGFR on the cell surface measured by image correlation spectroscopy. Eur. Biophys. J. 37:469–81 [Google Scholar]
  83. Srivastava M, Petersen NO. 83.  1996. Image cross-correlation spectroscopy: a new experimental biophysical approach to measurement of slow diffusion of fluorescent molecules. Methods Cell Sci. 18:47–54 [Google Scholar]
  84. Sergeev M, Costantino S, Wiseman PW. 84.  2006. Measurement of monomer-oligomer distributions via fluorescence moment image analysis. Biophys. J. 91:3884–96 [Google Scholar]
  85. Baumgartel V, Ivanchenko S, Dupont A, Sergeev M, Wiseman PW. 85.  et al. 2011. Live-cell visualization of dynamics of HIV budding site interactions with an ESCRT component. Nat. Cell Biol. 13:469–74 [Google Scholar]
  86. Sergeev M, Swift JL, Godin AG, Wiseman PW. 86.  2012. Ligand-induced clustering of EGF receptors: a quantitative study by fluorescence image moment analysis. Biophys. Chem. 161:50–53 [Google Scholar]
  87. Godin AG, Costantino S, Lorenzo LE, Swift JL, Sergeev M. 87.  et al. 2011. Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis. Proc. Natl. Acad. Sci. USA 108:7010–15 [Google Scholar]
  88. Swift JL, Godin AG, Dore K, Freland L, Bouchard N. 88.  et al. 2011. Quantification of receptor tyrosine kinase transactivation through direct dimerization and surface density measurements in single cells. Proc. Natl. Acad. Sci. USA 108:7016–21 [Google Scholar]
  89. Barbeau A, Godin AG, Swift JL, De Koninck Y, Wiseman PW, Beaulieu JM. 89.  2013. Quantification of receptor tyrosine kinase activation and transactivation by G-protein-coupled receptors using spatial intensity distribution analysis (SpIDA). Methods Enzymol. 522:109–31 [Google Scholar]
  90. Wiseman PW, Brown CM, Webb DJ, Hebert B, Johnson NL. 90.  et al. 2004. Spatial mapping of integrin interactions and dynamics during cell migration by image correlation microscopy. J. Cell Sci. 117:5521–34 [Google Scholar]
  91. Hebert B, Costantino S, Wiseman PW. 91.  2005. Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells. Biophys. J. 88:3601–14 [Google Scholar]
  92. Toplak T, Pandzic E, Chen L, Vicente-Manzanares M, Horwitz AR, Wiseman PW. 92.  2012. STICCS reveals matrix-dependent adhesion slipping and gripping in migrating cells. Biophys. J. 103:1672–82Provides capabilities and limitations of STICCS; shows matrix-dependent transport mechanisms of adhesion proteins. [Google Scholar]
  93. Kolin DL, Ronis D, Wiseman PW. 93.  2006. k-Space image correlation spectroscopy: a method for accurate transport measurements independent of fluorophore photophysics. Biophys. J. 91:3061–75 [Google Scholar]
  94. Brinkmeier M, Dorre K, Stephan J, Eigen M. 94.  1999. Two-beam cross-correlation: a method to characterize transport phenomena in micrometer-sized structures. Anal. Chem. 71:609–16 [Google Scholar]
  95. Dittrich PS, Schwille P. 95.  2002. Spatial two-photon fluorescence cross-correlation spectroscopy for controlling molecular transport in microfluidic structures. Anal. Chem. 74:4472–79 [Google Scholar]
  96. Jaffiol R, Blancquaert Y, Delon A, Derouard J. 96.  2006. Spatial fluorescence cross-correlation spectroscopy. Appl. Opt. 45:1225–35 [Google Scholar]
  97. Blom H, Johansson M, Hedman AS, Lundberg L, Hanning A. 97.  et al. 2002. Parallel fluorescence detection of single biomolecules in microarrays by a diffractive-optical-designed 2×2 fan-out element. Appl. Opt. 41:3336–42 [Google Scholar]
  98. Gosch M, Serov A, Anhut T, Lasser T, Rochas A. 98.  et al. 2004. Parallel single molecule detection with a fully integrated single-photon 2×2 CMOS detector array. J. Biomed. Opt. 9:913–21 [Google Scholar]
  99. Ohsugi Y, Kinjo M. 99.  2009. Multipoint fluorescence correlation spectroscopy with total internal reflection fluorescence microscope. J. Biomed. Opt. 14:014030 [Google Scholar]
  100. Kannan B, Har JY, Liu P, Maruyama I, Ding JL, Wohland T. 100.  2006. Electron multiplying charge-coupled device camera based fluorescence correlation spectroscopy. Anal. Chem. 78:3444–51 [Google Scholar]
  101. Burkhardt M, Schwille P. 101.  2006. Electron multiplying CCD based detection for spatially resolved fluorescence correlation spectroscopy. Opt. Express 14:5013–20 [Google Scholar]
  102. Matsumoto M, Sugiura T, Minato K. 102.  2007. Spatially resolved fluorescence correlation spectroscopy based on electron multiplying CCD. Proc. SPIE 6630:663017 [Google Scholar]
  103. Colyer RA, Scalia G, Rech I, Gulinatti A, Ghioni M. 103.  et al. 2010. High-throughput FCS using an LCOS spatial light modulator and an 8×1 SPAD array. Biomed. Opt. Express 1:1408–31 [Google Scholar]
  104. Colyer RA, Scalia G, Villa FA, Guerrieri F, Tisa S. 104.  et al. 2011. Ultra high-throughput single molecule spectroscopy with a 1024 pixel SPAD. Proc. SPIE 7905:790503 [Google Scholar]
  105. Kloster-Landsberg M, Herbomel G, Wang I, Derouard J, Vourc'h C. 105.  et al. 2012. Cellular response to heat shock studied by multiconfocal fluorescence correlation spectroscopy. Biophys. J. 103:1110–19 [Google Scholar]
  106. Needleman DJ, Xu Y, Mitchison TJ. 106.  2009. Pin-hole array correlation imaging: highly parallel fluorescence correlation spectroscopy. Biophys. J. 96:5050–59 [Google Scholar]
  107. Kannan B, Guo L, Sudhaharan T, Ahmed S, Maruyama I, Wohland T. 107.  2007. Spatially resolved total internal reflection fluorescence correlation microscopy using an electron multiplying charge-coupled device camera. Anal. Chem. 79:4463–70 [Google Scholar]
  108. Sisan DR, Arevalo R, Graves C, McAllister R, Urbach JS. 108.  2006. Spatially resolved fluorescence correlation spectroscopy using a spinning disk confocal microscope. Biophys. J. 91:4241–52 [Google Scholar]
  109. Axelrod D. 109.  2013. Evanescent excitation and emission in fluorescence microscopy. Biophys. J. 104:1401–9 [Google Scholar]
  110. Huisken J, Swoger J, Del Bene F, Wittbrodt J, Stelzer EH. 110.  2004. Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305:1007–9 [Google Scholar]
  111. Sankaran J, Manna M, Guo L, Kraut R, Wohland T. 111.  2009. Diffusion, transport, and cell membrane organization investigated by imaging fluorescence cross-correlation spectroscopy. Biophys. J. 97:2630–39Introduces theoretical basis and technical requirements and shows proof of principle of ITIR-FCS in experiments in live cells. [Google Scholar]
  112. Wohland T, Shi X, Sankaran J, Stelzer EH. 112.  2010. Single plane illumination fluorescence correlation spectroscopy (SPIM-FCS) probes inhomogeneous three-dimensional environments. Opt. Express 18:10627–41Provides the first integration of SPIM and imaging FCS to measure dynamics in a zebrafish embryo. [Google Scholar]
  113. Capoulade J, Wachsmuth M, Hufnagel L, Knop M. 113.  2011. Quantitative fluorescence imaging of protein diffusion and interaction in living cells. Nat. Biotechnol. 29:835–39Presents an improved SPIM-FCS setup with isotropic observation volume; live-cell investigation. [Google Scholar]
  114. Liu H, Dong C, Huang X, Ren J. 114.  2012. Spatially resolved scattering correlation spectroscopy using a total internal reflection configuration. Anal. Chem. 84:3561–67 [Google Scholar]
  115. Oh D, Zidovska A, Xu Y, Needleman DJ. 115.  2011. Development of time-integrated multipoint moment analysis for spatially resolved fluctuation spectroscopy with high time resolution. Biophys. J. 101:1546–54Introduces the theoretical basis and technical requirements and shows proof of principle of TIMMA in experiments in live cells. [Google Scholar]
  116. Sanden T, Persson G, Thyberg P, Blom H, Widengren J. 116.  2007. Monitoring kinetics of highly environment sensitive states of fluorescent molecules by modulated excitation and time-averaged fluorescence intensity recording. Anal. Chem. 79:3330–41 [Google Scholar]
  117. Widengren J. 117.  2010. Fluorescence-based transient state monitoring for biomolecular spectroscopy and imaging. J. R. Soc. Interface 7:1135–44 [Google Scholar]
  118. Sanden T, Persson G, Widengren J. 118.  2008. Transient state imaging for microenvironmental monitoring by laser scanning microscopy. Anal. Chem. 80:9589–96 [Google Scholar]
  119. Geissbuehler M, Spielmann T, Formey A, Marki I, Leutenegger M. 119.  et al. 2010. Triplet imaging of oxygen consumption during the contraction of a single smooth muscle cell (A7r5). Biophys. J. 98:339–49Explains the TRAST principle in an application to study cell oxygenation. [Google Scholar]
  120. Spielmann T, Blom H, Geissbuehler M, Lasser T, Widengren J. 120.  2010. Transient state monitoring by total internal reflection fluorescence microscopy. J. Phys. Chem. B 114:4035–46 [Google Scholar]
  121. Spielmann T. 121.  2012. Transient state fluorescence microscopy—method development and biological applications: exploiting the dark states of fluorophores to measure oxygen concentrations, redox state, Förster resonance energy transfer and membrane viscosity PhD Thesis, KTH R. Inst. Technol., Stockholm [Google Scholar]
  122. Lingwood D, Simons K. 122.  2010. Lipid rafts as a membrane-organizing principle. Science 327:46–50 [Google Scholar]
  123. Lagerholm BC, Weinreb GE, Jacobson K, Thompson NL. 123.  2005. Detecting microdomains in intact cell membranes. Annu. Rev. Phys. Chem. 56:309–36 [Google Scholar]
  124. Digman MA, Gratton E. 124.  2009. Imaging barriers to diffusion by pair correlation functions. Biophys. J. 97:665–73 [Google Scholar]
  125. Cardarelli F, Gratton E. 125.  2010. In vivo imaging of single-molecule translocation through nuclear pore complexes by pair correlation functions. PLoS One 5:e10475 [Google Scholar]
  126. Hinde E, Cardarelli F, Digman MA, Gratton E. 126.  2010. In vivo pair correlation analysis of EGFP intranuclear diffusion reveals DNA-dependent molecular flow. Proc. Natl. Acad. Sci. USA 107:16560–65 [Google Scholar]
  127. Bag N, Sankaran J, Paul A, Kraut RS, Wohland T. 127.  2012. Calibration and limits of camera-based fluorescence correlation spectroscopy: a supported lipid bilayer study. Chemphyschem 13:2784–94 [Google Scholar]
  128. Kraut R, Bag N, Wohland T. 128.  2012. Fluorescence correlation methods for imaging cellular behavior of sphingolipid-interacting probes. Methods Cell Biol. 108:395–427 [Google Scholar]
  129. Wawrezinieck L, Rigneault H, Marguet D, Lenne PF. 129.  2005. Fluorescence correlation spectroscopy diffusion laws to probe the submicron cell membrane organization. Biophys. J. 89:4029–42 [Google Scholar]
  130. Destainville N. 130.  2008. Theory of fluorescence correlation spectroscopy at variable observation area for two-dimensional diffusion on a meshgrid. Soft Matter 4:1288–301 [Google Scholar]
  131. Lenne PF, Wawrezinieck L, Conchonaud F, Wurtz O, Boned A. 131.  et al. 2006. Dynamic molecular confinement in the plasma membrane by microdomains and the cytoskeleton meshwork. EMBO J. 25:3245–56Probes heterogeneity modulations by a large variety of pharmacological treatments in live-cell membranes. [Google Scholar]
  132. He HT, Marguet D. 132.  2011. Detecting nanodomains in living cell membrane by fluorescence correlation spectroscopy. Annu. Rev. Phys. Chem. 62:417–36 [Google Scholar]
  133. Billaudeau C, Mailfert S, Trombik T, Bertaux N, Rouger V. 133.  et al. 2013. Probing the plasma membrane organization in living cells by spot variation fluorescence correlation spectroscopy. Methods Enzymol. 519:277–302 [Google Scholar]
  134. Huang H, Pralle A. 134.  2011. Continuous monitoring of membrane protein micro-domain association during cell signaling. arXiv:1101.5087v1
  135. Bag N, Ali A, Chauhan VS, Wohland T, Mishra A. 135.  2013. Membrane destabilization by monomeric hIAPP observed by imaging fluorescence correlation spectroscopy. Chem. Commun. 49:9155–57 [Google Scholar]
  136. Sankaran J, Bag N, Kraut RS, Wohland T. 136.  2013. Accuracy and precision in camera-based fluorescence correlation spectroscopy measurements. Anal. Chem. 85:3948–54 [Google Scholar]
  137. Costantino S, Comeau JW, Kolin DL, Wiseman PW. 137.  2005. Accuracy and dynamic range of spatial image correlation and cross-correlation spectroscopy. Biophys. J. 89:1251–60 [Google Scholar]
  138. Wiseman PW, Petersen NO. 138.  1999. Image correlation spectroscopy. II. Optimization for ultrasensitive detection of preexisting platelet-derived growth factor-β receptor oligomers on intact cells. Biophys. J. 76:963–77 [Google Scholar]
  139. Milon S, Hovius R, Vogel H, Wohland T. 139.  2003. Factors influencing fluorescence correlation spectroscopy measurements on membranes: simulations and experiments. Chem. Phys. 288:171–86 [Google Scholar]
  140. Sanguigno L, Cosenza C, Causa F, Netti PA. 140.  2013. Accounting for misalignments and thermal fluctuations in fluorescence correlation spectroscopy experiments on membranes. Analyst 138:1674–81 [Google Scholar]
  141. Kolin DL, Costantino S, Wiseman PW. 141.  2006. Sampling effects, noise, and photobleaching in temporal image correlation spectroscopy. Biophys. J. 90:628–39 [Google Scholar]
  142. Sankaran J, Shi X, Ho LY, Stelzer EH, Wohland T. 142.  2010. ImFCS: a software for imaging FCS data analysis and visualization. Opt. Express 18:25468–81 [Google Scholar]
  143. Lange JJ, Wood CJ, Marshall WA, Maddera LE, Yu QE. 143.  et al. 2013. Correction of bleaching artifacts in high content fluorescence correlation spectroscopy (HCS-FCS) data. Proc. SPIE 8590:859006 [Google Scholar]
  144. Skinner JP, Chen Y, Müller JD. 144.  2005. Position-sensitive scanning fluorescence correlation spectroscopy. Biophys. J. 89:1288–301 [Google Scholar]
  145. Rao R, Langoju R, Gosch M, Rigler P, Serov A, Lasser T. 145.  2006. Stochastic approach to data analysis in fluorescence correlation spectroscopy. J. Phys. Chem. A 110:10674–82 [Google Scholar]
  146. He J, Guo SM, Bathe M. 146.  2012. Bayesian approach to the analysis of fluorescence correlation spectroscopy data I: theory. Anal. Chem. 84:3871–79 [Google Scholar]
  147. Guo SM, He J, Monnier N, Sun G, Wohland T, Bathe M. 147.  2012. Bayesian approach to the analysis of fluorescence correlation spectroscopy data II: application to simulated and in vitro data. Anal. Chem. 84:3880–88 [Google Scholar]
  148. Eggeling C, Ringemann C, Medda R, Schwarzmann G, Sandhoff K. 148.  et al. 2009. Direct observation of the nanoscale dynamics of membrane lipids in a living cell. Nature 457:1159–62 [Google Scholar]
  149. Hedde PN, Dorlich, RM, Blomley R, Gradl D, Oppong E. 149.  et al. 2013. Stimulated emission depletion-based raster image correlation spectroscopy reveals biomolecular dynamics in live cells. Nat. Commun. 4:2093 [Google Scholar]
  150. Dertinger T, Colyer R, Iyer G, Weiss S, Enderlein J. 150.  2009. Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI). Proc. Natl. Acad. Sci. USA 106:22287–92 [Google Scholar]
  151. Cox S, Rosten E, Monypenny J, Jovanovic-Talisman T, Burnette DT. 151.  et al. 2012. Bayesian localization microscopy reveals nanoscale podosome dynamics. Nat. Methods 9:195–200 [Google Scholar]

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