Measuring Förster Resonance Energy Transfer
Table 2 : FD FLIM analysis of the FRET standards. FRET Standard a
2-component lifetime (Fraction)
Turquoise-5aa-Amber 3.9 ns (0.99) Turquoise-TRAF-Venus 3.6 ns (0.99) Turquoise-5aa-Venus 3.2 ns (0.73) 1.2 ns (0.27)
Tau(f) (±SD) b
Tau(α) c ±SD X 2 d E FRET e
3.9±0.03 NA NA NA
a Expressed in cells at 37º, n=6 cells. b Tau(f) is the average lifetime. c Tau(α ) is the amplitude-weighted lifetime. d Chi-square for the fi t of measurements at 12 frequencies from 10 to 120 MHz. e Determined using Eq. 1
FRET experiments, there will be a different ratio of the labeled proteins in each co-transfected cell. The donor-to- acceptor ratio influences the E FRET because cells expressing predominately donor-labeled proteins will have little or no FRET, whereas cells with an excess of acceptor have the potential for high FRET signals [ 4 , 11 ]. Therefore, the ratio of donor- to acceptor-labeled proteins must be accounted for in the analysis of data from intermolecular FRET experi- ments. The FLIM system used here has two-channels that simultaneously detect the emission signals from the donor and acceptor ( Figure 2 ). By measuring the mean intensity in both the donor ( I D ) and the acceptor ( I A ) channels, the ratio of the acceptor- to the donor-labeled proteins can be qualita- tively determined. Then, the measurement of the quenched donor lifetime in the same ROI allows the determination of E FRET (Eq. 1 ) at that I A / I D ratio.
Here the FRET-FLIM approach is used to quantify the heterologous protein interactions between the basic-leucine zipper (BZip) domain of the transcription factor C/EBPα and the heterochromatin protein 1 alpha (HP1α ). In earlier studies, we demonstrated that HP1α and C/EBPα interact, but only when the proteins are bound to heterochromatin [ 11 ]. For these intermolecular FRET measurements, the lifetime for the BZip domain labeled with Turquoise (the unquenched donor) was determined in regions of hetero- chromatin (typically 5 to 10 ROI per cell nucleus) for 10 different cells, yielding an average unquenched donor lifetime of 3.89±0.08 ns. Intensity images and lifetime measurements were then acquired from cells co-producing the mTurquoise-BZip domain and HP1α proteins labeled the acceptor FP, Venus ( Figure 6A ). As a control for potential non-specific interactions, measurements were also made from cells producing the mTurquoiseN1 protein (localized in both cytoplasm and nucleus) and Venus-HP1α (nuclear, see Figure 6B ). The lifetime map in Figure 6B demonstrates the quenched lifetimes of the Turquoise-BZip domain co-expressed with the Venus-labeled HP1α , indicated by cooler colors on the look-up table. In contrast, the lifetime of the TurquoiseN1 protein was not changed when co-expressed with Venus-HP1α ( Figure 6B ). To charac- terize the interaction between mTurquoise-BZip domain proteins and Venus-HP1α , the E FRET was determined from lifetime measurements of 15 cells co-producing the proteins at different I A / I D ratios ( Figure 6C ). The results show the dependence of E FRET between BZip domain and HP1α in
2015 May •
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3.5±0.01 3.9 10% 2.2±0.06 1.1 43%
regions of heterochromatin on the I A / I D
ratio, indicating the close proximity of fluorophores labeling the proteins ( Figure 6C ). In contrast, there was no change in the lifetime of mTurquoiseN1 with increasing Venus-HP1α .
Discussion
The development of quanti- tative imaging techniques to visualize cellular events inside living cells continues to provide critical tools for biomedical research.
The combination of FD FLIM measurements and phasor analysis described here enables a variety of quantitative approaches to interrogate events inside living cells. For example, in addition to the intermolecular FRET measure- ments illustrated above, the FLIM approach with phasor analysis is an outstanding method to monitor the activities of FRET-based biosensor probes that report intracellular signaling events [ 7 ]. A distinct advantage of the phasor plot approach is that multi-component lifetimes that occur in populations of proteins involved in FRET are immedi- ately evident from lifetime distributions that fall inside the universal semicircle. As can be seen in Figure 5C , this is also true for the linked FRET standard proteins, as well as similarly designed biosensor probes. The reason the linked probes also have multi-component lifetimes is that the FPs rotate slowly relative to their fluorescence lifetime, so there is negligible change in their relative orientations during the excited-state lifetime. This will give rise to heterogeneity in population of dipole orientations, leading to a distribution of E FRET for the linked FRET standard [ 14 ].
A general limitation of the FRET-FLIM approach described here is the necessity of producing the exogenous proteins of interest labeled with the FPs inside living cells, which can potentially cause artifacts associated with overexpression. T is concern is not unique to FLIM; it is shared with many diff erent types of cellular assays and requires careful control experi- ments. For example, where possible it is important to verify that FP-labeled proteins co-localize with their endogenous counterparts using immunostaining. It is also critical to verify that the FP-labeled proteins or biosensor probes accurately report cellular events using approaches such as mutagenesis. T e overexpression of the FP-labeled proteins or biosensor probes can potentially interfere with the cellular processes that they are designed to measure. T e FPs described here have been engineered to optimize their characteristics for expression and imaging in living cells and are well tolerated in living systems [ 1 ]. In addition, the imaging system has single-molecule detection sensitivity, which has allowed us to complement the FRET-FLIM with FCCS measurements [ 11 ]. Signifi cantly, the FLIM approach is not limited to exogenously labeled proteins. T e measurement of intrinsic autofl uorescence signals from living cells by FLIM and the analysis by phasor plot have been used to generate metabolic fi ngerprints from cells, allowing the identifi cation of diff erentiating cells or cancer cells according to their metabolic state [ 15 , 16 ].
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