Technical Notes

Fluorescence Lifetime (FLT)

Ewald Terpetschnig1 and David M. Jameson2
1ISS Inc.
2Department of Cell and Molecular Biology
John A. Burns School of Medicine
1960 East-West Rd.
University of Hawaii, HI 96822-2319

Principles

The fluorescence lifetime is a measure of the time a fluorophore spends in the excited state before returning to the ground state by emitting a photon [1]. The lifetimes of fluorophores can range from picoseconds to hundreds of nanoseconds. A list of the some commonly used fluorophores and their fluorescence lifetimes are given in Table 1.

Fluorophore Lifetime [ns] Excitation Max [nm] Emission Max [nm] Solvent
ATTO 655 3.6655690Water
Acridine Orange 2.0500530PB pH 7.8
Alexa Fluor 488 4.1494519PB pH 7.4
Alexa Fluor 647 1.0651672Water
BODIPY FL 5.7502510Methanol
Coumarin 6 2.5460505Ethanol
CY3B 2.8558572PBS
CY3 0.3548562PBS
CY5 1.0646664PBS
Fluorescein 4.0495517PB pH 7.5
Oregon Green 488 4.1493520PB pH 9
Ru(bpy)2(dcpby)[PF6]2 375458650Water
Pyrene > 100 341376Water
Indocyanine Green 0.52780820Water
Rhodamine B 1.68562583PB 7.8

Table 1. Commonly used fluorophores and their fluorescence lifetimes.

If a population of fluorophores is excited, the lifetime is the time it takes for the number of excited molecules to decay to 1/e or 36.8% of the original population according to:

Formula 1

Figure 1

As shown in the intensity decay figure, the fluorescence lifetime, t, is the time at which the intensity has decayed to 1/e of the original value. The decay of the intensity as a function of time is given by:

It = α e-t/τ

Where It is the intensity at time t, α is a normalization term (the pre-exponential factor) and τ is the lifetime.

Knowledge of the excited state lifetime of a fluorophore is crucial for quantitative interpretations of numerous fluorescence measurements such as quenching, polarization and FRET.

Excited state lifetimes have traditionally been measured using the “time domain” method or the “frequency domain” method.

Time-domain method

In the time domain method, the sample is illuminated with a short pulse of light and the intensity of the emission versus time is recorded. Originally, these short light pulses were generated using flashlamps that had widths on the order of several nanoseconds.

Modern laser sources can now routinely generate pulses with widths on the order of picoseconds or shorter.

Figure 2

If the decay is a single exponential and the lifetime is long compared to the exciting light, then the lifetime can be determined directly from the slope of the curve. If the lifetime and the excitation pulse width are comparable, some type of deconvolution method must be used to extract the lifetime.

Great effort has been expended on developing mathematical methods to “deconvolve” the effect of the exciting pulse shape on the observed fluorescence decay (see, for example, many chapters in [2]). With the advent of very fast laser pulses these deconvolution procedures became less important for most lifetime measurements, although they are still required whenever the lifetime is of comparable duration to the light pulse.

Frequency-domain method

In frequency-domain the excitation frequency E(t) is described by:

tan φ = ωτ

Figure 3

The modulations of the excitation (ME) and the emission (MF) are given by:

Formula 4

Formula 5

The relative modulation, M, of the emission is then:

Formula 6

τ can also be determined from M according to the relation:

Formula 7

Thus using the phase shift and relative modulation one can determine a phase lifetime τp and a modulation lifetime τM.

If the fluorescence decay is a single exponential, then τp and τM will depend upon the modulation frequency, i.e.,

τP (ω1) < τP (ω2) if ω1 > ω2

The differences between τp and τM and their frequency dependence form the basis of the methods used to analyze for lifetime heterogeneity, i.e., the component lifetimes and amplitudes.

One must be careful to distinguish the term fractional contribution to the total intensity (f) from α, the pre-exponential term referred to earlier in the time domain. The relation between these two terms is given by:

Formula 9

where j represents the sum of all components, α their pre-exponential factors and τ are the lifetimes of these components.

Analysis

Multifrequency phase and modulation data are usually analyzed using a non-linear least squares methods in which the actual phase and modulation ratio data (not the lifetime values) are fitted to different models such as single or multiple exponential decays. The quality of the fit is then judged by the reduced chi-square value (χ2):

Formula 10

where P and M refer to phase and modulation data, respectively, c and m refer to calculated and measured values and σP and σM refer to the standard deviations of each phase and modulation measurement, respectively. f is the number of modulation frequencies and d is the degrees of freedom.

In addition to decay analysis using discrete exponential decay models, one may also choose to fit the data to distribution models. In this case, it is assumed that the excited state decay characteristics of the emitting species actually results in a large number of lifetime components. Shown below is a typical lifetime distribution plot for the case of a single tryptophan containing protein – Human Serum Albumin.

Figure 4
Figure 5

The plots show the frequency response curves (phase and modulation vs. modulation frequency) for Human Serum Albumin (left). The excitation source was a 300-nm UV-LED; the emission was collected through a WG320 high-pass filter at a temperature of 20°C. Lifetime analysis was performed using a Lorentzian distribution (center at 5.4 ns, width = 2.9 ns, fractional distribution = 98%) and a second discrete component (t = 0.51 ns and fractional contribution = 0.02%). For a review of HSA lifetime studies see [3].

The distribution shown here is Lorentzian, but depending on the decay kinetics of the system, different types of distributions, e.g., Gaussian, or asymmetric distributions (Planck), may be utilized. This approach to lifetime analysis is described in [4].

Applications

Fluorescence Lifetime Assays: The fluorescence lifetime (FLT) has been widely utilized for the characterization of fluorescence species and in biophysical studies of proteins, e.g. the distances between particular amino-acid residues by Foerster Resonance Energy-Transfer (FRET). FLT is a parameter that is mostly unaffected by inner filter effects, static quenching and variations in the fluorophore concentration. For this reason FLT can be considered as one of the most robust fluorescence parameters, and therefore it is advantageous in clinical and high throughput screening (HTS) applications where it is necessary to discriminate against the high background fluorescence from biological samples. Also FLT offers more leverage with regards to multiplexing. The ability to discriminate between two fluorophores with similar spectra but different lifetimes is another way to increase the number of parameters to be measured (see, for example [5]).

Several mechanisms can be utilized for the development of lifetime-based assays. There are the simple binding assays, where binding of 2 components (one being fluorescently labeled) is accompanied by a FLT-change. Another scenario would be a quench-release type assay where the quenched species has low but finite fluorescence but is initially present in large excess. If the fluorescence compound is released (binding to a complementary DNA strand (Molecular Beacon) or by an enzymatic reaction) the lifetime of the system increases. Finally, FLT is a powerful method to measure energy transfer efficiency in FRET (fluorescence resonance energy transfer) assays, circumventing the issue of spectral cross talk between donor and acceptor, by using a non-fluorescent acceptor.

Fluorescence Lifetime Sensing: Most of the fluorescence sensors and assays that are in use today are based on intensity measurements. Though these methods are easier to implement they lack robustness and they require frequent calibration [6]. Many difficulties that are associated with intensity-based measurements can be circumvented using lifetime-based measurements. Lifetime-based measurements have the advantage that they are independent of the fluorescence intensity. In past 10 years many probes that exhibit analyte-sensitive fluorescence lifetime changes have been identified and characterized. Some of these probes are listed in Table 2. For a detailed discussion on lifetime-based sensing we refer you to the book chapter “Lifetime-based Sensing” in [6].

Fluorescence Lifetime Imaging: Fluorescence lifetimes also offer opportunities in fluorescence microscopy where the local probe concentration cannot be controlled. FLIM allows image contrast to be created based on the fluorescence lifetime of a probe at each point of the image. Typical examples are the mapping of cell parameters such as pH, ion concentrations or oxygen saturation by fluorescence quenching, fluorescence resonance energy transfer (FRET), or photon-induced energy transfer (PET). Examples of biological applications of lifetime imaging technology include scanning of tissue surfaces, photodynamic therapy, DNA chip analysis, skin imaging and others (see, for example [7]).

Fluorescent Probes Mean Lifetime [ns] Absorption Max [nm] Emission Max [nm]
  freeboundfreeboundfreebound
a) Calcium Probes  
Fura-2 1.091.68362335500503
Indo-1 1.41.66349331482398
Ca-Green 0.923.66506506534534
Ca-Orange 1.202.31555555576576
Ca-Crimson 2.554.11588588610612
Quin-2 1.3511.6356336500503
 
b) Magnesium Probes  
Mg-Quin-2 0.848.16353337487493
Mg-Green 1.213.63506506532532
 
c) Potassium Probe  
PBFI 0.520.59350344546504
 
d) Sodium Probe  
Sodium Green 1.132.39507507532532
 
e) pH Probes  
SNAFL-1 1.193.74539510616542
Carboxy-SNAFL-1 1.113.67540508623543
Carboxy-SNAFL-2 0.944.60547514623545
Carboxy-SNARF-1 1.510.52576549638585
Carboxy-SNARF-2 1.550.33579552633583
Carboxy-SNARF-6 1.034.51557524635559
Carboxy-SNARF-X 2.591.79575570630600
Resorufin 2.920.45571484587578
BCECF 4.493.17503484528514

Table 2. Spectral properties (absorption and emission maxima) and mean lifetimes of common ion-probes.

Books and Book Chapters related to Fluorescence Lifetime

  1. 1. Lakowicz, J.R. (1999). Principles of Fluorescence Spectroscopy, 2nd Edition, Kluwer Academic/Plenum Publishers, New York.
  2. 2. Valeur, B. (2002). Molecular Fluorescence. Wiley-VCH Publishers.
  3. 3. Herman B. (1998). Fluorescence Microscopy, 2nd Edition, Springer-Verlag, New York.
  4. 4. Baeyens W.R.G., de Keukeleire, D., Korkidis, K. (1991). Luminescence techniques in chemical and biochemical analysis, M. Dekker, New York.
  5. 5. Jameson, D. M. and Hazlett, T.L. (1991). Time-Resolved Fluorescence in Biology and Biochemistry, in Biophysical and Biochemical Aspects of Fluorescence Spectroscopy (Dewey, Ed.) Plenum Press, New York.

References

  1. Weber, G. in Hercules, D.M. Fluorescence and Phosphorescence Analysis. Principles and Applications, Interscience Publishers (J. Wiley & Sons), New York, pp. 217-240 (1966).
  2. Cundall, R.B. and Dale, R.E. (Eds.). Time-Resolved Fluorescence Spectroscopy in Biochemistry and Biology (Nato Advanced Science Institutes Series. Series a, Life Sciences; Vol. 69, Plenum Pub Corp, New York (1983).
  3. Helms, M.K., Petersen, C.E., Bhagavan, N.V., Jameson, D.M., Time-resolved fluorescence studies on side-directed mutants of human serum albumin. FEBS letters, 408, 67-70 (1997).
  4. Alcala, J. R., Gratton E. and Prendergast, F.G., Fluorescence lifetime distributions in proteins. Biophys. J. 51, 597-604 (1987).
  5. Gratton E. and Jameson, D.M., New approach to phase and modulation resolved spectra. Anal. Chem. 57, 1694-1697 (1985).
  6. Szmacinski H. and Lakowicz, J.R., Topics in Fluorescence Spectroscopy: Vol. 4. Probe Design and Chemical Sensing Lakowicz, J.R. (Ed.), Plenum Press, New York, (1994).
  7. Clegg, R. M. Holub, O., and Gohlke, C., Fluorescence lifetime-resolved imaging: measuring lifetimes in an image. Methods Enzymol. 360, 509-542 (2003).