3.1 Calibration Standards for Measuring E
The goal of the current study is to establish whether weak dimerization of the FPs affects the interaction between two FP-labeled proteins. To describe FRET in terms of interaction between estrogen receptors (alpha isoform, ERα
) tagged with the dimer-capable and monomeric forms of CFP and YFP, we must determine the proportion of the ERs in the interacting complex (Y
) in relationship to the concentration of one of the interacting factors (X
) according to the curve Y
). As discussed in Sec. 4.4, Y
can be represented by E
(the proportion of donor energy lost to energy transfer), provided assumptions are met. By contrast, the acceptor bleed-through-corrected FRET/donor value (F
) does not precisely describe Y
, since the F
values are nonlinear with respect to E
. Inserting Eq. (5)
into Eq. (7)
shows that F
is inversely proportional to (1–E
). Therefore, measuring interaction between two interacting factors will be aided by converting the F
values into E
requires calibrating the equipment according to previously defined calibration parameters.19,36
Calibration determines a series of instrument-specific constants (outlined in Sec. 2.4) that describe the relative abilities of different fluorescent outputs to be detected in different channels. Calibration is achieved by measuring the F
values for a series of calibration standards of known E
. The calibration standards described in this study were based on a series of dual-labeled androgen receptors (AR) containing CFP fused to the AR amino terminus and YFP fused to the AR carboxy terminus. We previously showed by using F
measurements that there is almost no energy transfer within the CFP-AR-YFP fusion protein (hereafter listed simply as AR) when present in cells grown in the absence of hormone.27
By contrast, energy transfer was detected in cells treated with the hormone dihydrotestosterone, which causes a conformational shift in the AR. We also found that a series of four AR point mutations, found in prostate cancer tumors that no longer responded clinically to androgen deprivation therapy, showed variable levels of energy transfer in response to no ligand, dihydrotestosterone, the antiandrogens hydroxyflutamide and Casodex, and two hormones that AR does not normally respond to: estradiol and progesterone (Ref. 27
, unpublished data). The different combinations of ligands and AR mutants created a series of thirty, almost identical, protein/ligand standards that provided a range of FRET responses with which to calibrate the equipment.
We first established that the CFP and YFP-tagged AR was an appropriate calibration control for the later studies of the CFP and YFP-tagged ERα. Bleed-through controls for the singly labeled ARs were not significantly different (p>0.05) from those obtained for the singly labeled ERs (). The similar behavior of CFP and YFP attached to the AR and ER validates the use of the AR standards for calibration of our ER studies.
As outlined in Sec. 2.4, calibration required the collection of F/D and A/D measurements for all 30 different AR/ligand calibration standards. As an example, the F/D  and A/D  measurements are shown for cells treated with one of the ligands, 10−6 M progesterone. The F/D and A/D ratios were calculated for the wild-type AR (black line) and various mutant ARs (V715M cyan line; H874Y blue line; T877A dark blue line; T877A light blue line) as the slopes of the graphs of the (background-subtracted and acceptor bleed-through-corrected) FRET or acceptor channel fluorescence intensities, in each ROI, against the donor channel intensity. For a dual-labeled standard that contains the same relative levels of Donor and Acceptor, we observed that control values determined by linear regression (rather than simply averaging the ratios calculated for each individual ROI) minimized experiment-to-experiment variations in F/D or A/D measurement arising from experiment-to-experiment variations in background correction.
Fig. 3 Establishment of calibration constants to convert acceptor-bleedthrough-corrected FRET/donor (F/D) measurements into the proportion of donor transferred to acceptor (E). Background-subtracted and acceptor bleed-through corrected intensity measurements (more ...)
As we previously reported,27
ratio of the wild-type AR in cells treated with progesterone [black slope in ] was only marginally increased above that obtained with the AR labeled only with the donor (yellow slope). This indicated little energy transfer within the dual-labeled wild-type AR. By contrast, the four mutants responded abnormally, and variably, to progesterone. As expected, the energy transfer detected as an increase in F
 was paralleled by an increase in A
The mean F/D and A/D ratios from the six independent calibration studies of the progesterone-treated cells are listed in (insets). By F/D measurement, each of the different standards shown in have significantly different (p>0.05) levels of energy transfer. By contrast, there was a much higher variation in the A/D measurements than in the F/D measurements. This variation also was visible in the much higher scatter of the A/D data points from the best fitting slope (see ; r2=0.984±0.014 for F/D compared to 0.958±0.027 for A/D). We do not know the origin of the variation in the A/D measurement, but suspect that the F/D measurement, which incorporates two variables affected by FRET (F and D), may be less affected by random FRET measurement error than A/D, in which only the D variable is affected by FRET. It also is possible that the “sensitized emission” component of energy transfer, read in the FRET channel, may be more accurately detected than other components of the FRET signal. Regardless of origin, the F/D measurement is clearly a more reproducible indicator of energy transfer. For calibration, errors that might be introduced by the relatively inaccurate A/D measurement can be minimized by collecting a large number of data points in a number of independent experiments.
3.2 Calibration of kfD, kfaD, and kaD
For the current calibration studies, 19,178 different calibration ROIs, and 1030 bleed-through control ROIs, were collected in six independent studies. kfD
, the ability of the equipment to detect Donor fluorescence in the FRET channel relative to the donor channel, is represented by the FRET channel bleed through from the control cells expressing AR-CFP only. In the six AR calibration studies, kfD
averaged 0.5625 (95% CI from 0.5459 to 0.5795). kfaD
(the ability of the equipment to detect donor energy transferred to the acceptor in the FRET channel) and kaD
(the ability of the equipment to detect equimolar amounts of donor and acceptor) were calibrated, as described in Sec. 2.4, by plotting the F
values obtained from the 30 calibration controls against A
. According to Eq. (8)
, the y
intercept (−1.1129±0.0910) described kfaD
as 1.6756 (95% CI from 1.4891 to 1.8617), when kfD
is 0.5625. According to Eq. (9)
, the slope (1.3421±0.0616) described kaD
as 1.2485 (95% CI from 1.2246 to 1.2682).
Using these equipment-specific calibration constants, E
was determined from the F
] and A
] measurements for each of the 30 calibration standards. Plotting those E
values against each other  provided a best-fitting straight line of slope of 0.993 with a y
intercept of zero. This is near to the slope of 1.000 expected if, on average, the E
values measured by F
correspond to those measured by A
. Since the values were generated from the same set of F
data used to derive the constants, the near unity of the data is expected. More importantly, the distribution of the 30 calibration data points around the slope was normal (p>0.10), which provided some validation for the calibration values obtained despite the large scatter. As noted before, the significant scatter in the graph (r2
=0.928) likely originates from the much lower statistical confidence in the A
measurements than in the F
measurements, which was compensated for by the use of large sets of calibration data.
3.3 Automated Removal of Cell Debris Artifacts
The measurements of interaction, described next, rely on the more accurate F/D ratio. Still, some form of quality control must be implemented to ensure that the data points are accurate. Images were collected from cells coexpressing ERα-CFP and ERα-YFP or coexpressing ERα-mCFP and ERα-mYFP (the monomeric variants). The cells were treated for 30 min either with 10−8 M estradiol or with an equivalent amount of ethanol (0.01%) before image collection. ROIs were drawn automatically around regions of contiguous ERα-CFP (or ERα-mCFP) fluorescence emitted from the cell nucleus. ROIs with donor intensity below 100 units (on a 12-bit scale) above background were excluded. ROIs also were excluded when the amount of background-subtracted fluorescence collected in the acceptor channel at 50-ms integration time was not between 0.235 to 0.265 that collected at 200 ms. This 0.25 exclusion was done only for ROIs with measurable amounts of acceptor fluorescence, defined as >200 fluorescent units on a 12-bit scale. These ROIs likely represented cells that moved during collection. Only 0.2% of cells were excluded by this criterion, as this intensity ratio was generally very close to 0.25 (see ).
After the initial exclusions, a number of ROIs remain that do not represent real cells. Most of those false objects generally represent yellow autofluorescent debris excited by the same wavelengths of light used to excite CFP. This debris mimics fluorescent in the FRET channel and therefore shows artificially high E values. Retaining those false objects in the FRET analysis would introduce error, but removal of those false FRET objects by visual inspection of each image is impractical in large-scale analyses. For example, a total of 10,433 control and 11,929 experimental ERα-CFP-expressing ROIs were collected for the studies of .
The method used to mathematically remove the autofluorescent non-ERα objects incorporates other fluorescent properties of the autofluorescent debris. Since the autofluorescent debris is not well excited using the acceptor excitation wavelengths, these artifacts cluster at very low acceptor and high FRET amounts. Dividing the high E measurement by the low acceptor measurement should therefore result in very high qc-value for the autofluorescent debris (high E, low acceptor), but a low qc-value for cells expressing CFP. The qc-value distribution is shown in for one dataset. 108 of the 135 objects had a qc-value between 0.8×10−3 and −0.8×10−3 (closed boxes, mean of 0.2±0.2×10−3) and were included in subsequent analyses. By contrast, the excluded objects (open boxes) showed a very high scatter in qc-value with all of those objects localized in ROIs with very low acceptor levels. The excluded ROIs in also are clear outliers of the curve in (open boxes). As discussed in the next section, that curve is representative of the amount a complex formed between CFP-tagged and YFP-tagged ERα as a function of the amount of YFP-tagged ERα . The failure of the excluded objects to fit to that curve confirms their designation as “debris.” also highlights that the retention of those points during analysis would introduce significant error into measurements based on accurate curve fitting to the data points. For all the studies listed in the following sections, 7.6% of objects identified were categorized as debris according to the prior criteria and excluded from further analysis.
Fig. 4 Removal of autofluorescent debris. (a) For high throughput analysis with no user intervention, a quality control (qc) measurement was derived (Sec. 3.3) to identify ROIs (open boxes) that varied substantially from the ROIs representing actual cellular (more ...)
3.4 Describing E in Relationship to Biochemical Interaction
As shown in the example , the E
values for each ROI were graphed against the fluorescence intensity of the acceptor in the same ROI. The data points are expected to follow a biochemical relationship described by the formation of a complex at a constant amount of one factor (CFP-labeled in our example) with increasing amounts of the interacting factor (YFP-labeled in our example).25,27,36
The formula for this relationship, Y
), describes how the concentration of a complex (Y
) increases as a function of increasing concentrations of one of the interacting factors (X
). For FRET analysis, E
is assumed to represent a surrogate measurement of the proportion of the YFP-labeled factor in the complex, whereas the intensity of the acceptor is assumed to represent the concentration of the YFP-labeled factor. The merits of these and other assumptions are discussed in Secs. 4.3 and 4.4.
In the example provided, the quality-controlled data [, closed boxes] fit to the binding curve with an R2 value of 0.92. By contrast, inclusion of the debris in the data (open boxes) resulted in an R2 value of questionable significance (0.51). For the quality-controlled data, a runs test showed that no portions of the data were nonrandomly distributed above or below the curve. This suggests that the use of the one-site binding model for fitting the data points was appropriate (note that a two-site binding model did not fit well to the data by this criterion). Thus, the FRET data indeed appear to fit the binding model, which enabled the extrapolation of biochemical data to compare interaction of ERα labeled with dimer-competent and monomeric FPs. Experiment-to-experiment variations in the extent to which the data points fit the curve are discussed in later sections.
3.5 Interaction of ERα with Dimer-Competent Fluorescent Proteins is Retained with Monomeric Fluorescent Proteins
We compared the interaction of ERα-CFP and ERα-YFP (dimer-capable FPs) with the interaction of ERα-mCFP and ERα-mYFP (monomeric FPs) in cells treated or not with 10−8 M estradiol. E was graphed against acceptor intensity for each of those four conditions. The data from each of the five independent experiments are shown in each column of graphs in (experiment 1, 2, etc.). The studies of ERα-CFP/ERα-YFP and ERα-mCFP/ERα-mYFP interaction in the presence of estradiol are shown in . The parallel studies with no estradiol added are shown in . The side-by-side comparison of the curves of ERα interaction using the monomeric and dimeric FPs are shown in .
Within each plot, the data points were fit to the biochemical curve described earlier. Curve-fitting parameters are described in Sec. 2.5. The best-fitting curves for each dataset are shown as a solid line for the cells treated with estradiol  and as a dashed line for the cells treated with the drug vehicle [, in which the solid lines depicting interaction on estradiol treatment are displayed for comparison]. Values inserted into each graph show the number of ROIs used to draw the curve (n), the R2 value describing the goodness of fit of those data points to that curve, the P-value that shows whether the data points deviate consistently in certain regions away from the curve by a runs test (“P,runs”), and the P-value that shows whether the data points are normally distributed around each curve (“P,norl”). P,runs and P,norl values of less than 0.05 [shown in gray in ] are considered to show significant deviations from the curves.
In the absence of estradiol , the data points did not fit well to the bimolecular interaction curve for either the dimer-competent FPs (R2=0.43±0.11, mean ± SD of all five experiments) or for the monomeric FPs (0.53±0.11). No P,runs or P,norl values are shown for these curves, since the R2 values alone indicated that the data do not fit the curves. Visual inspection suggests a poorly fitting trend toward more FRET at higher acceptor levels. Thus, as a population of cells, dimer formation is inconsistent, at best, in the absence of estradiol.
By contrast, a good fit to the bimolecular interaction curve (, high R2 values) was observed for all cells treated with estradiol, regardless of whether FRET was measured using the dimer-competent FPs  or the monomeric FPs . Within each experiment, the data points fit somewhat better (p=0.04) to the curve when the dimer-competent FPs were used (R2=0.85±0.05, mean ±SD of all five experiments) than when the monomeric FPs were used (R2=0.78±0.09). However, the P values for the runs test and test for normalcy showed that there was substantive experiment-to-experiment variation in the extent to which the data points distributed randomly around the curves. Visual inspection suggested that the curve fit is appropriate in all experiments, but that larger amounts of noise in experiments 2 and 4 led to poorer runs tests and poorer tests for normalcy.
3.6 No Consequence of Fluorescent Protein Dimerization on ERα-ERα Interaction Kinetics
The fit to the bimolecular interaction curves in the presence of estradiol permitted the extrapolation of the equilibrium dissociation constant (Kd) and the maximal amount of energy transfer at saturated binding (B max) for ERα-ERα interaction with dimer-competent and monomeric FPs. The Kd, which describes the relative on and off-rates of ERα-ERα interaction, was not statistically different for interaction using the dimer-competent or monomeric FPs. The Kd (±95% confidence intervals) derived from each of the five studies is shown in (experiment 1 to 5), together with the mean of all experiments. Experiment-to-experiment variation in the Kd was observed, which perhaps reflects day-to-day variation in some aspect of cell health or physiology. Still, on the same day, the Kds measured for both the FP- and mFP-tagged ERα interactions were the same.
Fig. 6 FP dimerization does not affect FRET measurement of the interaction kinetics of the estradiol-bound estrogen receptor (ERα) with itself. (a) For each of the five independent studies shown in , the amounts of acceptor required to reach half (more ...)
The maximal amount of energy transfer (Bmax) tended to be lower for the dimerization of ERα tagged with the monomeric FPs (p=0.05, i.e., at the margin of statistical significance). However, the uncertainty in the fits to the curve (poor runs test and poor tests for normalcy on some days) introduced an element of uncertainty in the B max measurements. With the nonrandomness of the data fit to the curve, the marginally different B max levels may reflect nothing more than a higher number of poor quality data points collected with the monomeric FPs.