Transcript Fluorescence correlation spectroscopy - UFCH JH

Fluorescence microscopy III
Fluorescence correlation spectroscopy
(FCS)
Detection volume in confocal microscopy:
the volume from which fluorescence is collected in a confocal (or a
multiphoton) is defined by the diffraction limited focusing and the
collection efficiency of the objective - Point spread function (PSF) of the
microscope
typically of femtoliter volume
In a diluted solution (~ nM)
the average number of
molecules in detection volume
~1
x ~ 200 nm
z ~ 1 mm
~ 3D Gaussian profile
The measured fluorescence
signal is then very noisy due to
fluctuations in the number of
molecules in detection volume,
their transitions to
nonfluorescent states (triplet,
…)
Autocorrelation of fluorescence fluctuations:
The timescale of fluorescence fluctuation provides information on the
kinetics of the underlying processes. They are studied by correlation
analysis.
t1
t1
t2
G (t)
fluorescence intensity
t1
t1/2
t2
t1
t [ms]
t [ms]
G(t ) 
I(t )  I(t  t )
I(t )
2
1
t1/2 – characteristic timescale of the fluctuations
Note: Sometimes a different definition of G (t) – converges to 1!!!
Timescale of fluctuations in FCS:
The timescale of fluorescence fluctuation provides information on the
kinetics of the underlying processes. They are studied by correlation
analysis.
rotational movement
G (t)
photophysical processes
(triplet state, …)
antibunching
diffusion
t [ms]
A single fluorophore molecule emits photons with intervals which are related to its
lifetime. More fluorophores in a complex can emit with shorter intervals –
investigation of antibunching provides information on molecular oligomerization
from Schwille and Haustein: Fluorescence Correlation Spectroscopy
Free diffusion and FCS:
The autocorrelation function G (t) is fitted by a theoretical model
For free diffusion (e.g. in a solution) and assuming a 3D Gaussian shape of
the detection volume following model has been derived:
1/2


1
1
1


G(t ) 
N 1  (t / t D )  1  (t / t D )(0 / z ) 
1/N
G (t)
x direction
tD
z direction
t [ms]
Number of molecules and diffusion
time in detection volume
z/0 – structure parameter, usually ~ 5-8
Free diffusion and FCS:
The autocorrelation function G (t) is fitted by a theoretical model
When considering the transition to triplet state:
1/2


1
1
1


G(t )  1  T  T exp(t / t T )
N(1  T ) 1  (t / t D )  1  (t / t D )(0 / z ) 
fraction of molecules in triplet
characteristic time of triplet transition
When considering more fluorophore species with different diffusion times:
GM (t ) 
 Q  F g (t )
i 1
2
i
i
i


N  Qi Fi 
 i 1

M
2
brightness
fraction
tD1
1/2


1
1


gi (t ) 

1  (t / t Di )  1  (t / t Di )(0 / z ) 
G (t)
M
tD2
t [ms]
Diffusion coefficient D determination:
Diffusion coefficient D of the fluorophore can be calculated from its
diffusion time tD
2
0
D
4t D
The detection volume diameter 0 is usually determined by a calibration
measurement with a solution of a fluorophore with known diffusion
coefficient
for example Rhodamine 6G has D = 426 mm2s-1
In a similar manner concentration can be calculated from N and the
detection volume size
DNA compaction investigated by FCS:
E1
DNA molecules have pharmaceutical potential in gene therapy, they are however
large and negatively charged – difficult transport over cellular membrane
Natural solution – compaction of DNA by polycationic molecules such as spermine
(+4)
amonium/phosphate ratio
DNA labelled by intercalating dye PicoGreen is condensed by spermine and the
required ration of condenser/base-pair is searched
Particle number decreases as the multiple-labelled DNA becomes smaller than the
detection volume
Adjimatera et al. (2006) Pharm Res 23:1564-1573
Dual-color fluorescence cross-correlation spectroscopy
(FCCS):
Simultaneous measurement of FCS of 2 different fluorophores excited by 2
different lasers. The emission is divided by an emission dichroic mirror to 2
channels and detected by 2 detectors with appropriate emission filters.
detector
major dichroic (double)
emission dichroic
GCC (t ) 
Normalized Intensity
1,0
0,8
I A (t )  IB (t  t )
I A (t ) IB (t )
1
Problems:
0,6
o crosstalk between the two excitation
and detection channels
0,4
0,2
0,0
400
Autocorrelation of
individual fluorophores and
cross-correlation between
them can be measured
450
500
550
600
650
700
Wavelength [nm]
750
800
o difference in detection volumes in the
two channels (diffraction limited focus
is larger for longer wavelength)
Dual-color fluorescence cross-correlation spectroscopy
(FCCS):
E2
Cross-correlation is related to interactions of molecules.
Positive cross-correlation indicates that molecules move together (complex). The
higher the amplitude of the cross-correlation, the higher complex concentration
Negative cross-correlation (anti-correlation) – molecules avoid each other
Interaction of 2 membrane proteins:
negative control – noninteracting
molecules, only crosstalk
positive control – double-labeled protein
Experiment:
Liu et al. (2007) Biophys J 93:684-698
Fluorescence lifetime correlation spectroscopy (FLCS):
Uses differences in fluorescence lifetime (instead of in fluorescence spectra) to
distinguish contributions to FCS signal
Lifetime is sensitive to fluorophore environment  FLCS can separate contributions
from fluorophores in different environments (different conformation of proteins, …)
The method combines FCS with pulsed time-resolved fluorescence spectroscopy
(typically TCSPC), arrival time on 2 different scales is measured for each photon
photon
Laser pulse
2480
1240
3120
Relative Time [ps]
100000
4500
4600
4700
4800
40000
Correlation G(t)
Macro Time [ns]
60000
Counts
4900
1,12
80000
1,08
1,04
20000
1,00
0
0
10
20
30
Channel Time [ns]
40
50
1E-3
0,01
0,1
1
10
Lag Time t [ms]
100
1000 10000
Fluorescence lifetime correlation spectroscopy (FLCS):
Each component has its characteristic fluorescence decay (decay pattern)
Statistical (numerical) filters (instead of optical filters) are use to separate the
photons according to their arrival time after the excitation pulse
5 ns component
5 ns comp
2 ns component
2 ns comp
0,01
1E-3
(i)
1E-4
1E-5
1E-6
1E-7
1E-8
5
4
3
2
1
0
-1
-2
-3
-4
5 ns component
5 ns
2 ns component
2 ns
Filter ffjj(i)
Filter
Normalized pattern pj
(i)
0,1
0
200
400 600 800 1000 1200
Channel j
For each channel j the measured
intensity Ij is a linear combination
of patterns:
Ij t   w1 t pj1  w2 t pj2
0
200
400 600
800
Channel j
1000
The probability with photons in jth
channel contribute to ith pattern.
Sum over i equals 1 for each j.
Fluorescence lifetime correlation spectroscopy (FLCS):
Optical filters can improve the data by filtering out scattered light. The statistical
filters can do the same – scattered light and noise can be filtered out thanks to their
different decay pattern
Filter fj(i)
5 ns component
2 ns component
afterpulsing
Dark counts (detector afterpulsing)
results in a constant background –
influence correlation at short lag times
(can be misinterpreted as triplet
transition)
Channel j
Note: after separating the contributions of individual patterns we can find
autocorrelation for each of them and cross-correlations between them
If we do not know one of the patterns (it cannot be measured individually), we can
still separate the respective contribution by filtering out everything else
DNA compaction investigated by FLCS:
E3
What is the compaction mechanism (gradual or all-or-none transition)? For large
DNA molecules investigated by single-molecule fluorescence microscopy, but for
smaller plasmids below resolution
The lifetime of PicoGreen changes upon compaction (change in local polarity)
Patterns for uncondensed (4 ns) and fully condensed (3 ns) DNA measured
separately and used for investigation of the titration midpoint by FLCS
DNA compaction investigated by FLCS:
E3
Patterns for uncondensed (4 ns) and fully condensed (3 ns) DNA measured
separately and used for investigation of the titration midpoint by FLCS
G(t)
2.4
1.6
10
-3
t (ms)
10
2
Good agreement of the autocorrelation of the filtered out components with the pure
forms  equilibrium between uncondensed and fully condensed form at the
midpoint (all-or-none transition)
Analysis of cross-correlation between the 2 components reveals further details
Humpolíčková et al. (2008) Biophys J 94:L17-L19
DNA compaction investigated by FLCS:
E3
Analysis of cross-correlation between the 2 components reveals further details
G(t)
60
30
10
-4
t (ms)
10
1
Its amplitude between the amplitudes of the two components suggests presence of
dynamics between the two forms.
Fitting with a model indicates dynamics on ms scale with independent compaction of
approximately 5 domains in the DNA molecule.
FLCS also showed that another DNA condenser HTAB (+1) exhibits gradual
compaction mechanism
Humpolíčková et al. (2008) Biophys J 94:L17-L19
E4
FLCS and lifetime tuning:
Not always is the process we investigate accompanied by a sufficient
change in lifetime.
Fluorescence lifetime can be influenced externally for example by the
vicinity of a conductive surface (quenching)
1.8 ns in supported lipid bilayer (SLB) on ITO surface
5.6 ns in small unilamellar vesicles (SUVs)
G (t) G(t)
Correlation
2.5
SLBs
SUVs
filtred SUVs
filtred SLBs
2.0
FLCS
1.5
1.0
0.01
0.1
100
10
1
Time t [ms]
tLag
[ms]
1000
FCS of planar samples:
In planar samples (lipid bilayers, molecular layers on interfaces, …) the
detection volume is reduced to a 2-dimensional Gaussian intensity profile
G(t ) 
1
1
N 1  (t / t D )
2
0
2mm
0 ≈ 200 nm

D
4t D
4nm
Determination of 0 is a problem:
o positioning problem: small axial
displacement – significant change in ,
N and tD.
o difference in detection volume in the
reference and the sample due to
difference in refractive index
A need to avoid extrinsic calibration by introducing an intrinsic ruler
Calibration-free FCS:
extrinsic calibration avoided by introducing an intrinsic ruler:
• axial step between several FCS measurements – Z-scan FCS
• parameters of continuous scanning during the FCS measurement –
scanning FCS, scanning continuously over a circle of known radius or a
line with a defined speed
• distance between more points in which FCS is simultaneously measured,
multiple measurement points can be generated by:
two overlapping foci generated by doubling the focus by a Wollaston
prism (like in DIC) or Michelson interferometer – 2-focus FCS.
different pixels of a microscope image (recorded for example in TIRF
configuration) – Image correlation spectroscopy (ICS, STICS, …)
• combination of scanning and imaging in laser scanning microscopy (LSM)
– known pixel size and scanning speed – RICS, STICS, …
Z-scan FCS:
known axial step between measurements serves as intrinsic calibration
14
14
12
12
10
10
8
8
6
6
4
4
2
2
0
-0,8
tD [ms]
DZ
Particle number
parabolic dependence of 2, N and tD on DZ:
0
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,8
0,6
DZ [mm]
2
0 
2 DZ 2 
t D (DZ ) 
1 2 4 ,

4D 
 0 
2
2 


D
Z
N(DZ )   cS 0 1  2 4 

 0 

2
Determination of surface concentration cS and diffusion coefficient D of the fluorophore
ICS:
spatial correlation between image pixels (distances along x and y axes play the role
of lag time)
The amplitude of the correlation peak is
inversely proportional to fluorophore
density
additional temporal information allows investigation of diffusion:
• correlations between images in a temporal series (spatio-temporal ICS – STICS)
diffusion – broadening of the peak
oriented flow – broadening + shift
t
possibility to construct velocity maps
temporal resolution defined by imaging
speed
• imaging by LSM with defined scanning speed  spatial correlation contains
temporal information (Raster image correlation spectroscopy – RICS), 2 axes – 2
timescales
Hebert et al. (2005) Biophys J 88:3601-3614
Acknowledgement
The course was inspired by courses of:
Prof. David M. Jameson, Ph.D.
Prof. RNDr. Jaromír Plášek, Csc.
Prof. William Reusch
Financial support from the grant:
FRVŠ 33/119970