Fluorescence Correlation Spectroscopy and Frster Resonance Energy - PowerPoint PPT Presentation

Fluorescence Correlation Spectroscopy and Förster Resonance Energy Transfer Thorsten Wohland

Interaction of Light with Matter luminescence

Internal Conversion Excited Singlet State S 1 Triplet State T 1 Ground Energy State S 0 VR IC VR Absorption Fluorescence VR : vibrational relaxation IC : Internal Conversion

Intersystem Crossing Excited Singlet State S 1 Triplet State T 1 Ground Energy State S 0 VR ISC Photochemical VR reaction Absorption Delayed Phosphorescence Fluorescence Fluorescence VR : vibrational relaxation ISC : Intersystem Crossing

Lifetimes, rate constants, and quantum yield Excitation rate k ex ~I  k nr Lifetime Quantum yield  1        f  k k nr nr

Fluorescence Properties • Wavelength (absorption and emission) • Lifetime (of various states) • Quantum yield • Polarization 6 http://micro.magnet.fsu.edu

F-techniques Fluorescence Anisotropy Fluorescence Lifetime Fluorescence Recovery after Single Particle Tracking Photobleaching 7

Förster Resonance Energy Transfer - FRET 8

The actual formula for the FRET rate orientation       2 9000 ln 10     Q          4 D ( ) k r F d     T D A 6 5 4   r 128 N n D A 0 Note: Formula is now in SI units! Spectral overlap distance environment Donor lifetime 6   1 R R 0 is the so-called Förster radius . It is the    0 k ( r ) distance at which a FRET pair exhibits 50%  T   r FRET. It is a constant for any FRET-pair. D k 6 R   T E 0 E   1   k 6 6 R r D T 0 Förster Distance Calculator

FRET to monitor conformational changes of a virus  Donor: Alexafluor 488 TFP (AF488) labelled protein layer  Acceptor: DiI labelled lipid bilayer Far Donor – Acceptor Near Donor – Acceptor  Low FRET  High FRET  High fluorescence  Lower donor intensity fluorescence  High average donor intensity  Lower average lifetime donor lifetime 10

Lifetime experiment Higher FRET at 25˚C 1 𝜐 𝐸 = 1.0 Γ + 𝑙 𝑜𝑠 + 𝑙 𝑈 0.8 Intensity (a.u.) IRF Trace at 25  C 0.6 Trace at 37  C 1.0 0.4 2x10 5 400 Intensity (kcts) 0.8 0.2 Intensity (cnts) Intensity (cnts) 300 Overall Decay 0.6 0.0 ROI Decay 0 5 10 15 25˚C Fitted Curve 1x10 5 200 Time (ns) IRF 0.4 100 0.2 0.75 0.45  2 (High FRET population)    Low FRET population  0 0 0.0 Intensi 0 30 60 90 120 150 180 0 0 5 5 10 10 15 15 20 20 0.70 0.40 Time (s) Time (ns) Time (ns) 0.65 0.35 1.0 2x10 4 3x10 5 0.60 0.30 Intensity (kcts) 0.8 Intensity (cnts) Intensity (cnts) 0.55 0.25 2x10 5 0.6 ROI Decay 25  C 37  C Overall Decay 37˚C 1x10 4 Fitted Curve Temperature IRF 0.4 1x10 5 3.2 DV2 at 25  C 0.2 DV2 at 37  C 3.0 0 0 0.0 0 30 60 90 120 150 180 0 0 5 5 10 10 15 15 20 20 Time (s) Time (ns) Time (ns)  avg (ns) 2.8 2.6 2.4 2.2 25  C 37  C Temperature 11

Temperature dependence of lipid bilayer-protein coat distance 25 to 37ºC DV2 (NGC) transition vs temperature in absence of MgCl 2 DV2 (NGC) transition vs temperature in absence of MgCl 2 a 1 (low FRET population) 3.6 a 2 (High FRET population) 25  C to 37  C (Donor only) 0.75 3.4 0.40 3.2 0.70 25  C to 37  C  avg (ns) 0.35 37  C to 25  C 3.0 0.65 0.30 2.8 2.6 0.60 0.25 37  C to 25  C (Dual lablelled) 2.4 25  C to 37  C (Dual lablelled) 0.55 0.20 24 26 28 30 32 34 36 38 24 26 28 30 32 34 36 38 Temperature (  C) Temperature (  C) 12

Single particle spectroscopy State 2 State 1 Mg 2 + Imaged under TIRF microscope 13

Single particle spectroscopy Donor Acceptor Donor Acceptor Overlay iSMS 14

Single particle spectroscopy Molecule 1 Molecule 2 Molecule 3 5 Background 7 5 Donor Intensity Donor Donor 6 4 4 5 4 3 3 3 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Time(s) Time(s) Time(s) 7.5 9 7.5 Background Acceptor Acceptor Acceptor Intensity 7.0 7.0 8 6.5 6.5 7 6.0 6.0 6 5.5 5.5 5.0 5 5.0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Time(s) Time(s) Time(s) 1.0 0.6 Acceptor intensity Donor Intensity 0.6 0.8 Overlay 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Time(s) Time(s) Time(s) 1.0 1.0 1.0 0.8 0.8 0.8 E FRET 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Time(s) Time(s) Time(s) 15

Single particle spectroscopy FRET Efficiency population Graph 1600 1400 k21 1200 Observations k12 1000 800 600 400 200 0 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 FRET Efficiency (E) 1.0 1.0 1.0 HMM Fitting 0.8 0.8 0.8 E FRET 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Time(s) Time(s) Time(s) Dwell time histogram of HJ from Open to closed state Dwell time histogram of HJ from Closed to open state 2500 1600 2000 1200 Counts Counts n = 29 n = 29 1500 k21 Close  Open = 4.3  0.1 s -1 k21 Open  Closed = 3.4  0.1 s -1 800 1000 400 500 0 0 0 1 2 3 4 0 1 2 3 4 Time(s) Time(s) 16 (ref: Sean A. McKinney1 et. al . 2002)

Summary 1 • FRET can measure distances in the range of ~10 nm • It can be measured either be observing the emission wavelength or best by lifetimes • It can be done in ensembles or on a single molecule level • Here we demonstrated its application to viral conformations and holiday junction dynamics 17

Fluorescence Correlation Spectroscopy (FCS) • What are fluctuations? • What are correlations? • How to calculate correlations? • Fluorescence Correlation Spectroscopy (FCS) • FRET-FCS • Fluorescence Cross-Correlation Spectroscopy (FCCS) • Imaging FCS/FCCS

Fluctuations A + B AB equilibrium kinetics [AB] fluctuations Time fluctuations 19

FCS: General idea • What is a correlation • Predicting the future • Self-similarity

Correlations   a b a b  g 1 Anti-correlation  a b   g g 1 No correlation a b  Correlation g 1 X. Shi and T. Wohland, “ Fluorescence Correlation Spectroscopy ”, in Nanoscopy, CRC Press, 2010

Example B A Probability 0 1 0.25 <A> = 0.5 <B> = 0.5 1 1 0.25 <AB> = 0.25 0 0 0.25 <AB> = 1 <A><B> 1 0 0.25 22

Example B A Probability 0.3 <A> = 0.5 <B> = 0.5 0.2 <AB> = 0.2 0.2 <AB> = 0.8 <A><B> 0.3 23

Example B A Probability 0.1 <A> = 0.5 <B> = 0.5 0.4 <AB> = 0.4 0.4 <AB> = 1.6 <A><B> 0.1 24

Correlations 1. Correlated variables   a b a b a 1 1 0 1 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0  b     a ; a b 1 1 1 1 1 1 0 1 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 0 b 2 2 2 4 2. Anticorrelated variables   a b a b a 1 1 0 0 1 0 1 0 1 1 1 0 1 0 0 0 1 0 1 0  b     a 0 ; a b 1 1 1 b 0 0 1 1 0 1 0 1 0 0 0 1 0 1 1 1 0 1 0 1 2 2 4 3. Uncorrelated variables   a b a b a 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0  b    1  a a b 1 ; 1 1 b 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2

Autocorrelations           a t a t a t a t               a t a t a t a t        a t a t     G       a t a t             F t F t F t F t      G     Stationary     2 F t F t F t Processes

Short time shifts               F t F t ? F t F t Blue: F(t) Yellow: F(t+  ) Time F   F                         F F t t t t F F F F t t t t 1 2 3 The intensity peaks always overlap to some extent and thus               F t F t F t F t

Long time shifts               F t F t ? F t F t Blue: F(t) Yellow: F(t+  ) Time F   F                         F F t t t t F F F F t t t t 1 2 3 The intensity trace contains a random pattern of intensity peaks. Therefore an overlap of all/many peaks is only achievable at short times.               F t F t F t F t