Fitting Model for Diffusion in 3D Fit by 3D Gaussian Model: Aragon & Pecora J. Chem. Phys. 64, (1976) ICS: D cm 2 s -1

Diffusing Population: 2D System Simulation: =10 spatial = -1 = ± 0.03 temporal = g(0,0,0) -1 = ± 0.01 Autocorrelation Function Amplitude: Number Density Simulation: D = 0.01  m 2 s -1 ; =10

Diffusing Population: 2D System D 2D = ±  m 2 s -1 Best Fit with 2D Diffusion Model Simulation: D = 0.01  m 2 s -1 ; =10

Flowing Population & Diffusing Population 2D Simulation: diff =5 flow =5 spatial = -1 = ± 0.03 temporal : diff =4.9 ± 0.3 flow =5.1 ± 0.3 Autocorrelation Function Amplitude: Number Density Simulation: D = 0.01  m 2 s -1 ; diff =5 |v| =  m s -1 ; flow =5

Flowing Population & Diffusing Population 2D D 2D = ±  m 2 s -1 |v| = ±  m s -1 Best Fit with 2D Two population Diffusion & Flow Model Simulation: D = 0.01  m 2 s -1 ; diff =5 |v| =  m s -1 ; flow =5

2-Photon ICS on Living Cells 10  m CHO Cell:  Actinin/EGFP Plated on Fibronectin Two-photon fluorescence microscopy 7.5 min 37 °C Quantify Dynamics & Clustering…

2-Photon ICS on Living Cells 10  m Region 1 64x64 pixels Diffusion & Flow & Immobile 3 Populations D 2D = ±  m 2 s -1 |v| = 1.12 ± 0.07  m min -1 10% Immobile Diff = 2.6 ± 0.2  m -2 flow = 0.33 ± 0.04  m -2 Immobile = 0.34 ± 0.03  m -2

2-Photon ICS on Living Cells 10  m Region 2 128x128 pixels Diffusion & Immobile 2 Populations D 2D = 4.7± 0.3 x10 -4  m 2 s -1 21% Immobile Diff = 7.6 ± 0.3  m -2 Immobile = 2.0 ± 0.2  m -2

Transport Map for  -actinin in a Living Cell 10  m Fraction Immobile Fraction Diffusing Fraction Flowing 10 min Diffusion Dist. 10 min Flow Dist. Wiseman et al. Journal of Cell Science 117, , 2004 Highlighted in Nature Reviews Mol. Cell Biol. Vol 5, 953, 2004

2P-Image Cross-Correlation Spectroscopy (ICCS) t=0t=1t=2t=n Biological Sample Auto1Auto2Cross Temporal Correlation Spatial Correlation Wiseman et al., J. Microscopy 200, (2000)

Temporal Two-photon ICCS  Actinin - CFP  5 Integrin-YFP 10  m 2-Photon Imaging: 10 min,  t = 5s, 3 hr after plating CHO-K1 Cells on 10  g/mL FN Ex. 880 nm Em. 485 & 560 nm 2D Diffusion2D Flow Crosstalk Corrected

Spatio-Temporal Image Correlation Spectroscopy Calculate r 11 ( , ,  )  Central Peak is r 11 (0,0,  ) t=0 t=1 t=2 t=3 r 11 ( , ,  ) r 11 (0,0,  )    Hebert et al. Biophys. J (2005)

Full Space Time Correlation on Living Cells Directed Flow of  -actinin at the basal membrane Hebert et al. Biophys. J (2005) Raw Data Immobile Filtered r(0,0,  ) Correlation Peak Tracking i) ii) Δt=15s 45s 75s 105s 135s A) B) C) 1 μm r(  ) 

Vector Maps of  -actinin MEF Cell TIRF Microscopy Time 100 s with Images sampled at 0.1 Hz Dr. Claire Brown and Ben Hebert

Vector Maps of  -actinin 0 μm/min 9 μm/min 5 μm 0 s2.8 s1.5 s r(  ) r(  ) Ff Inverse relationship b/w retrograde flow & protrusion speed (similar to actin)

Quantum Dots…Nanoparticles Photostable…Different sizes…Different Colours Colored Marker Tags for Molecules CdSe Core ZnS Cap Surface Functionalized Quantum Dot: Semiconductor Materials 10 nm Silicon &Germanium Based Quantum Dots

Particle Tracking of QD Labeled AMPA Receptors Richard Naud (Wiseman Group) with Prof. Paul DeKoninck Laval University 20  m Rat Purkinje neuron Dendritic Spine and Synapse

‘Off’ state ‘On’ state (CdSe)ZnS – Streptavidin (QD605) TIRF Illumination CCD Detection 50ms Integration Time 2000 Frames Nirmal et al. Nature(London) (1996) But…Quantum Dots Blink! See Bachir et al. JAP 99 (2006) Affects ICS measurements Single Dot i(t) trace

Some New Things: kICS Point source fluorescence emitters Image series 2D Fourier transform of images k-space time correlation function Is This Just another Acronym? No! k-space Correlation has distinct advantages… For Photobleaching and Blinking of Fluorophores Special Thanks to Prof. David Ronis See Kolin et al. Biophysical Journal (2006)

Residuals Intercept Photophysics Slope Transport Properties Some New Things: kICS Transport Coefficients Independent of Photophysics Blinking or Photobleaching!

Determine the slopes for each value of τ, plot them as a function of τ : Residuals Intercept Slope Some New Things: kICS  D independent of  o No non-linear Curve fitting

Slope kICS Live cell measurement  5 integrin For a given :

Conclusions Fluctuations Contain Information about Molecules Fluctuation Size…Concentrations/Oligomerization Fluctuation Time…Dynamics/Kinetics FCS…Temporal Analysis of Fluctuations Image Correlation…Space & Time Analysis Quantum Dots…Promising…but not perfect!