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Chattopadhyay A, editor. Serotonin Receptors in Neurobiology. Boca Raton (FL): CRC Press; 2007.

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Chapter 2Monitoring Receptor-Mediated Changes of Intracellular cAMP Level by Using Ion Channels and Fluorescent Proteins as Biosensors

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INTRODUCTION

Five-hydroxytryptamine (5-HT or serotonin) is an important neuromodulator involved in a wide range of physiological functions. The effects of serotonin are mediated by a large family of receptors, either ionotropic or coupled to second-messenger cascades. With the exception of the 5-HT3 receptor, which is a cation channel, all 5-HT receptors belong to the superfamily of 7 transmembrane-spanning receptors that are coupled to multiple heterotrimeric G-proteins.

Many of the cellular responses mediated by serotonin do not involve activation of one particular second-messenger cascade but result from the functional integration of the networks of intracellular signaling pathways. To better understand serotonergic signaling, it is therefore important to have a broad palette of methodical approaches that allow specific analysis of signaling processes with high spatial and temporal resolution. Moreover, study of receptor functions within a living cell is required to extend results obtained by biochemical and pharmacological methods. Such measurements also allow real-time analysis of signaling processes in a single cell.

Cyclic AMP (cAMP) is a key second messenger that transmits information to many different effector proteins within the cell. The cellular cAMP level depends on the activity of two groups of enzymes, the adenylyl cyclases (AC) that produce cAMP and the phosphodiesterases (PDE) that hydrolyze cAMP (Beavo, 1995; Sunahara et al., 1996). Increased cAMP levels activate a number of different effector proteins, including protein kinase A (PKA) (Francis and Corbin, 1999), hyperpolarization-activated (Ih) channels (DiFrancesco, 1993), the guanine–nucleotide exchange factor Epac (de Rooij et al., 1998), and cyclic nucleotide-gated (CNG) channels (Finn et al., 1996). Metabotropic serotonin receptors coupled to Gs (5HT4 and 5HT7) or Gi/o proteins (5HT1 and 5HT5) regulate AC activity, thereby changing local cAMP concentration (Barnes and Sharp, 1999).

Because biochemical methods used for cAMP measurement lack both spatial and temporal resolution, detailed understanding of how information is transduced within cAMP-regulated signaling cascades is elusive. The classical approach to analyze the receptor-mediated change in cAMP concentration includes labeling of the cells with radioactive adenine followed by the calculation of the conversion rate of [3H]ATP to [3H]cAMP. Although this biochemical assay is very robust and reproducible, it can not provide information about the real-time course of the cAMP level. To answer this question, cAMP signals need to be measured within the dynamic environment of the living cell.

In this chapter, we concentrate on recently established methods allowing the quantitative measurement of the intracellular cAMP concentration in living cells with good spatial and temporal resolution. These will include two different approaches: (1) electrophysiological analysis to detect electrical currents mediated by cAMP-mediated activation/inactivation of hyperpolarization-activated, cyclic nucleotide-modulated ion channels (HCN) and (2) measurement of Förster Resonance Energy Transfer (FRET) by using fluorescent-labeled guanine nucleotide exchange factor (Epac) that is activated by direct binding of cAMP (Ponsioen et al., 2004).

MONITORING OF RECEPTOR MEDIATED cAMP CHANGES IN LIVING CELLS BY ELECTROPHYSIOLOGICAL APPROACH

Here, we will describe how to measure the intracellular cAMP concentrations using cAMP-modulated ion channels as a cAMP sensor. Because cAMP directly modulates the opening of certain ion channels such as CNG or HCN channels (Finn et al., 1996; Pape, 1996; Santoro and Tibbs, 1999; Wei et al., 1998), the measurement of their activity can be a useful tool to monitor receptor-mediated changes of intracellular cAMP concentrations.

CNG channels are fast-activating, voltage-independent nonselective cation channels. Depending on the membrane potential of the cell and the resting intracellular cAMP concentration, such channels induce a persistent ion current and can be used as a reporter of cAMP changes with high temporal and spatial resolution (Karpen and Rich, 2005). The measurement can be done using the whole cell patch clamp recordings or calcium imaging techniques. It is important to pay attention to the Ca2+-permeability of these channels, since Ca2+-ions can also mediate a stimulation or inhibition of several AC subtypes (Cooper, 2003). On the other hand, the Ca2+-permeability of CNG channels can be used to monitor channel activity by fluorescent Ca2+-indicators.

Generally, HCN channels are more sensitive to cAMP than the CNG channels (Finn et al., 1996; Santoro and Tibbs, 1999; Zagotta and Siegelbaum, 1996). For this reason, several CNG channels were genetically modified allowing for cAMP sensitivity (K1/2(cAMP) = 0.5–2 μM) similar to that obtained for natural HCN channels (Rich et al., 2001). In addition to unequal sensitivity to cAMP, CNG and HCN channels possess the different biophysical properties including channel activation and voltage dependence (Figure 2.1).

FIGURE 2.1. Functional cyclic nucleotide gated channels (CNG) and hyperpolarization-activated cyclic nucleotide-gated channels (HCN) are oligomers composed by four subunits.

FIGURE 2.1

Functional cyclic nucleotide gated channels (CNG) and hyperpolarization-activated cyclic nucleotide-gated channels (HCN) are oligomers composed by four subunits. The cyclic nucleotide binding domain (CNBD) is located close to the C-terminus of each subunit. (more...)

Experimental System, Setup, and Data Analysis

We have recently developed an experimental approach using slow activating, hyperpolarization-dependent nonspecific cation channels (HCN) as a cAMP sensor (Heine et al., 2002). The usage of the HCN channel allowed us to monitor steady-state levels and dynamic changes of cAMP. In examples described below, we used a member of the HCN-channel family, the HvCNG-channel, cloned from the antennae of the moth Heliothis virescens (Krieger et al., 1999) and expressed by baculovirus system in Spodoptera frugiperda (Sf.9) cells. Generally, we record HvCNG currents in the whole-cell patch-clamp mode, although the perforated patch configuration also can be used for such analysis (Rich and Karpen, 2002). In our experiments, we used the discontinuous single-electrode voltage-clamp amplifier SEC-05L from npi-Electronic (Tamm, Germany) connected with an ITC-16 interface from Instrutech (Greatneck, NY). This amplifier allows for a precise control over the voltage clamp of the cell independently from the access resistance. Such precise control is important, because cAMP measurement strongly depends on the voltage. For data acquisition and analysis we apply Pulse-PulseFit 8.31 software from HEKA (Lambrecht, Germany) and Igor-WaveMetrics software (Lake Oswego, OR). All measurements were performed using insect TC.100 medium as extracellular solution. In this medium it is possible to keep cells intact for 4 to 7 h at 25 ± 0.2°C. Because the possible role of Ca2+ ions in the modulation of channel activation kinetics still remains controversial (Budde et al., 1997; Luthi and McCormick, 1998), we routinely use the highly Ca2+-buffered (10 mM EGTA) pipette solution containing 15.3 nM free Ca2+ concentration.

The opening kinetics of HCN channels is modulated by cAMP (Figure 2.1), so the channel activation time constant can be used as readout for the intracellular cAMP concentration. This kinetic parameter is calculated by an exponential fit of the current activation at a defined voltage step (Figure 2.2) and is independent on the expression level of the channel in the outer membrane. HCN channels are not activated at the resting potential of nonexcitable cells (around –30 to –50 mV) and induce no steady state calcium influx over time. These particular biophysical properties are useful to calibrate the cellular system using defined cAMP concentrations and the activation time constant as a reporter of intracellular cAMP concentration (Figure 2.2B). A second parameter that is independent on the channel expression level is half-maximal activation voltage (V1/2). To calculate these parameters, we perform two types of fittings: an exponential fit of the time course of channel activation and a Boltzmann fit of the steady-state activation of tail currents. To fit the activation time constants we use the equation:

FIGURE 2.2. Measuring the intracellular cAMP-concentration using a recombinant HCN channel expressed in Sf.

FIGURE 2.2

Measuring the intracellular cAMP-concentration using a recombinant HCN channel expressed in Sf.9 cells. (A) Whole cell patch-clamp recordings were used to activate the channel by voltage step to –100 mV for 1 sec. The activation time constant (more...)

I(t)=I0+I1·[1-exp(-t/τ)],
2.1

where I0 is the current at the beginning of activation, and I1 is the maximal current at the end of the applied voltage pulses. The exponent t/τ represents the ratio between the time t and the activation time constant τ. For the Boltzmann fit of the steady-state activation curve of HvCNG current we used:

P(Vm)=1/{1+exp[(Vm-Vh)/k]},
2.2

where P[proportional, variant](Vm) denotes the steady-state open probability P[proportional, variant] of HCN channels at a membrane potential Vm, Vh is the half-activation voltage of the HCN current, and k is the slope factor. cAMP levels were calculated from the dose–response relationship (Figure 6.2), and the data for the dose–response curve were fitted by a Hill equation with variable slope

n=τmin+(τmax-τmin)/1+(c1/2/c)n,
2.3

where τmin is the time constant at 0 cAMP, τmax is the time constant at 1 mM cAMP, c1/2 is the half-maximal cAMP concentration, and n is the Hill factor. To calculate the cAMP concentration for each time constant between τmin and τmax, we converted the Hill equation to:

c=(τ-τmin)/(τmax-τmin)·c1/2n/{1-[(τ-τmin)/(τmax-τmin)](1/n)}
2.4

Based on the above strategy we determined values of Ka (concentration at half-maximum activation) = 0.62 μM for the half-maximal cAMP concentration, and n = 1.51 for the Hill coefficient. The Ka value was slightly lower than the Ka of 0.76 μM as previously reported by using inside–out patches (Krieger et al., 1999). On the other hand, the Ka determined in our system is in good agreement with measurements obtained from other heterologously expressed HCN channels (Ludwig et al., 1998; Santoro et al., 2000). These results confirm that the HvCNG channel represents a sensitive cAMP sensor and encouraged us to use this channel for the quantitative analysis of cAMP level in living cells.

Examples

The HvCNG channel expressed in Sf.9 cells was used as an endogenous sensor for cAMP changes induced by serotonin receptor activation. For that, the channel needs to be coexpressed together with appropriate receptor and G-proteins. We coexpress the HvCNG channels together with recombinant 5-HT4 receptor or 5-HT1A receptor and Gs-proteins (Gαs-, β1-, γ2-subunits) or Gi-proteins (Gαi2-, β1-, γ2-subunits), respectively.

Cells coexpressing all three components, e.g., HvCNG channels, 5-HT4 receptors, and Gs-protein revealed maximal activation of HvCNG channel-mediated currents 70 ± 4 sec after exposure to 0.1 μM 5-HT. The τa value was decreased from 769 ± 66 msec to 310 ± 38 msec, which correspond to an increase in cAMP concentration to 4.6 ± 1.45 μM. Noteworthy, the receptor activation could be repeated several times, although with a steadily declined response (Figure 2.3). Interestingly, τa values of some coinfected cells indicated that the intracellular cAMP level was elevated to 5 μM even under control conditions. This may indicate that overexpressed receptors reveal a basal activity that affects endogenous cAMP levels as has been previously described (Claeysen et al., 1999). On average, however, cAMP level of 1.9 ± 1.02 μMa = 467 ± 75 sec) was not significantly different from the basal cAMP levels of 1.5 ± 0.3 μMa = 571 ± 33 sec) obtained in Sf.9 cells that were only infected with the HvCNG channel.

FIGURE 2.3. Measurements of cAMP concentration after agonist-induced receptor activation.

FIGURE 2.3

Measurements of cAMP concentration after agonist-induced receptor activation. (A) Schematic drawing of the measurement configuration. (B) Coexpression of recombinant 5-HT4 receptors and HvCNG channels, together with the Gs-proteins, lead to a decrease (more...)

Importantly, this system is valid not only for measuring an increase but also a decrease of cAMP. Application of serotonin to the Sf.9 cells cotransfected with HvCNG channel, 5-HT1A receptor, and Gi-protein (Gαi2-, β1-, γ2-subunits) revealed a strong inhibitory response. In this case, the τa value increased from 545 ± 57 msec to 805 ± 41 msec and returned to 662 ± 32 msec after wash-out, which corresponds to a decrease of the cAMP level to 0.4 ± 0.06 μM (basal cAMP level was 1.5 ± 0.3 μM). The time delay to reach stable current kinetics was 183 ± 32 sec. It is notable that in experiments with serotonin receptors we often obtained some fluctuation of the τa values at the start of 5-HT application and during the wash-out. We suggest that these fluctuations may reflect the activity of intracellular factors modulating the HvCNG channel activation kinetic (e.g., AC, PDE, and protein phosphorylation), which we did not control in these experiments.

Conclusion

Taken together, the use of the HvCNG channel allows us to monitor steady-state levels and dynamic changes of cAMP. This analysis is further favored by its dual dependence on voltage and cAMP. The fact that opening of HCN channels is modulated by cAMP (Figure 2.1), enables us to use the activation time constant as readout of the intracellular cAMP concentration. The kinetic parameter is calculated by an exponential fit of the current activation at a defined voltage step (Figure 2.2) and is independent of the expression level of the channel. As the HCN channel is not activated at resting membrane potential, an overexpression of the channels will not lead to a persistent influx of Ca2+-ions and will not change the resting membrane potential of nonexcitable cells. These particular biophysical properties are useful to calibrate the cellular system using defined cAMP concentrations and to use the activation time constant as a direct reporter of intracellular cAMP concentrations (Figure 2.2). The activation time constant is highly sensitive over a broad concentration range of cAMP concentration (0.1–5 μM), which enables measuring even small changes in cAMP level. This sensor is useful to determine endogenous cAMP levels, changes induced by constitutively active receptors, and agonist-induced changes of cAMP (Ponimaskin et al., 2005; Ponimaskin et al., 2002).

However, usage of HCN sensors has several disadvantages. This method possesses the low temporal resolution due to the slow activation kinetic (1 to 5 sec) and the absolute need to use electrophysiological techniques to induce a defined hyperpolarization of the cell as a base to measure of the activation time constant (Heine et al., 2002). In addition, the measurements derived by HCN channels do not provide the information on the subcellular organization of intracellular cAMP changes, which are accessible with different fluorescent probes (Nikolaev and Lohse, 2006) or by the use of CNG channels (Karpen and Rich, 2005; Rich and Karpen, 2002). On the other hand, CNG channels monitor cAMP or cGMP levels as a function of current amplitudes (Rich et al., 2000; Santoro et al., 2000), which strictly depends on the expression level of the channel. Therefore, the use of CNG channels demands a difficult calibration of the level of CNG channel expression within each cell.

In conclusion, the choice of a suitable sensor is mainly dependent on the answers to specific questions. HCN channels are useful for measuring constitutive activity and total cAMP levels, whereas CNG channels are more useful to investigate the temporal and spatial dynamic of receptor induced cAMP changes.

FÖRSTER RESONANCE ENERGY TRANSFER (FRET)-BASED cAMP SENSOR

Here, we describe a more comfortable but not less sophisticated method to measure cAMP-level by using fluorescence-labeled sensors for cAMP detection. In this case, analysis of the Förster resonance energy transfer (FRET) between the fluorophores will provide information about changes in cAMP levels. To determine FRET, a fluorescence microscope, a CCD camera with computer, an image splitter, and some analyzing software are needed. The using of this approach will provide an experimenter with information about relative changes in cAMP concentrations with very good spatial and temporal resolution.

cAMP Sensors

Cyclic AMP is known to activate protein kinase A (PKA) and cyclic nucleotide-regulated ionchannels (CNG), as well as exchange proteins directly activated by cAMP (Epac). Therefore, these proteins have been used as a basis for the construction of fluorescence cAMP sensors (Adams et al., 1991; Zaccolo et al., 2000; Zaccolo and Pozzan, 2002). PKA was modified so that the catalytic subunit was labeled with yellow fluorescent protein (YFP) as donor, whereas the regulatory subunit was labeled with cyan fluorescent protein (CFP) as acceptor. It has been shown that the time resolution of this sensor was acceptable, but it lacked in reasonable FRET efficiency because both subunits were expressed independently. Such undefined stoichiometry results in reduction of the FRET appearance. The PKA-based sensor has an affinity of ~300 nM for cAMP binding (Bacskai et al., 1993) and very steep dose-response relation, which rapidly reaches saturation.

Recently, an Epac1-based (de Rooij et al., 2000; de Rooij et al., 1998; Kawasaki et al., 1998) cAMP sensors has been created. These constructs are composed of a single subunit and therefore possesses a higher FRET appearance. In our experiments, we use an Epac1 sensor described by Ponsionen and colleagues (Ponsioen et al., 2004). In this construct, amino terminus of Epac1 was fused to CFP, whereas carboxy terminus was fused to YFP. In addition, the DEP domain that is responsible for membrane localization of Epac1 was deleted. Binding of cAMP to the Epac construct leads to a conformational change of the Epac1 part of the protein, resulting in a distance and/or orientation change of CFP toward YFP (Figure 2.4). By using this sensor, Ponsionen and colleagues have demonstrated that reduction of intracellular cAMP leads to an increase of the energy transfer between CFP and YFP, whereas a rise of cAMP diminishes it (Figure 2.4). In contrast to the PKA-based sensor, an Epac1-based sensor shows cAMP affinity of 14 to 50 μM and is sensitive for an extended concentration range.

FIGURE 2.4. The model shows a conformational change of the Epac-construct (CFP-Epac(DEP-CD)-YFP) induced by cAMP binding to the regulatory domain of Epac.

FIGURE 2.4

The model shows a conformational change of the Epac-construct (CFP-Epac(DEP-CD)-YFP) induced by cAMP binding to the regulatory domain of Epac. (Adapted from Bos, J.L., Nat Rev Mol Cell Biol, 4, 738, 2003.) The distance between the two fluorophores increases (more...)

FRET Principles and FRET-Based Analysis

The Förster resonance energy transfer (FRET) is named after Theodor Förster, who described an energy-transfer between two (not necessarily the same) fluorophores with overlapping Dem/Aex (Förster, 1948). While the donor fluorophore is excited, it can transfer its energy under certain conditions to an acceptor fluorophore. This transfer results in excitation of the acceptor. In cases of fluorescent acceptors, an induced fluorescence emission can be observed. The energy transfer, however, is nonradiative. Therefore, the often-used term fluorescence resonance energy transfer is misleading and should be avoided. FRET can be described by dipole–dipole coupling mechanism. The efficiency E of the energy transfer depends on the distance r, and the orientation of the donor emission dipole moment and the acceptor absorption dipole moment. The strong distance-dependency is characterized by the Förster radius Ro at the half-maximal efficiency:

E(r)=Ro6Ro6+r6
2.5

In the case of the Epac construct we assume existence of two states: the first one is the unbound state DA, where cAMP is not bound to the construct, and the second one is the bound state D_A where cAMP is bound (Figure 2.4). Each state is characterized by a characteristic FRET efficiency. DA shows a high FRET efficiency, whereas D_A shows it low. In the presence of cAMP both states are populated in a certain ratio, depending on the cAMP concentration. A change in cAMP concentration will not influence the value of the FRET efficiencies but changes the population ratio between both states, resulting in a change of FRET appearance. FRET appearance of the Epac construct is therefore a function of the cAMP concentration present. Moreover it has been shown in vitro with the FRET analysis that a Hill kinetic could be used to explain the cAMP concentration dependent enzyme-activity of the Epac construct.

Generally, several methods are available to analyze FRET. The most sophisticated and accurate method is the measurement of the donor fluorescence lifetime. It will allow obtaining the FRET efficiency and the ratio between DA and D_A states in a quantitative manner. In contrast to many other techniques, this method is independent on the fluorophor concentration.

Other methods to analyze FRET are fluorescence intensity based. Here the appearance of FRET will result in a measurable decrease of donor intensity and an increase of acceptor intensity. This property can be used to analyze FRET and to investigate the cAMP concentration. A common intensity-based method which is applied on confocal laser scanning microscopes (cLSM) is the acceptor photobleaching method. Nevertheless, with this destructive method it is not possible to analyze changes of FRET appearance over time. Apart from the acceptor photobleaching method, laser scanning microscopes are often not ideal for kinetic measurements of FRET, because the high light intensity results in a fast bleaching of the donor as well as of the acceptor. Additionally, the scanning unit of the cLSM limits the frame rate of the microscope in a second range, resulting in a relatively poor time resolution compared to a wide field microscope with a CCD-camera (where frame rates up to 100 Hz are available).

With the aim to analyze fast changes of cAMP levels in living cells, different intensity-based methods, by which emission intensities of CFP and YFP are compared continuously are more favorable than the acceptor photobleaching method. It consists of a wide field microscope and a fast EMCCD camera allowing fast frame rates and therefore a high time resolution. It also overcomes the problem of destructive bleaching because it operates with much lower light intensities than a cLSM and is therefore more physiological. In order to obtain both emission intensities of CFP and YFP simultaneously, an image splitter has to be installed between the microscope and the camera containing two sets of filters for CFP and YFP emission.

A widely used algorithm to calculate FRET has been proposed by Gordon (Gordon et al., 1998) for measuring with only two sets of emission filters and one excitation wavelength. The ratio between the emission intensities deriving from CFP (Ffa) and those deriving from YFP (Dfd), Ffa/Dfd is used as a FRET equivalent measure, whereas FRET is inversely proportional to the ration. Because of the spectral overlap of CFP and YFP emission, these intensities cannot be measured directly. Consequently, spectral unmixing has to be applied. Taking a closer look at the emission spectra of CFP and YFP, it becomes apparent that an emission band for CFP can be chosen to exclude YFP emission. However, CFP emission cannot be excluded from YFP emission, and there is always a fraction (“cross talk”) of CFP emission passing the YFP filter set. To calculate the cross talk of CFP in the emission light of the YFP filter set we applied the following considerations: with only CFP as a sample, the light intensity (Fd) of CFP emission in the YFP filter set is divided by the light intensity (Dd) of CFP emission in the CFP filter set. For our conditions:

Fd/Dd=0.63
2.6

With a similar procedure having only YFP as a sample, the cross-talk of YFP in the emission light of the YFP filter set can be obtained. However, as mentioned above, we chose a spectral band of our CFP filter set that no YFP emission could pass through.

Therefore we had:

Da/Fa=0
2.7

where Da is the light intensity of YFP emission in the CFP filter set and Fa the light intensity of YFP emission in the YFP filter set.

If the measured light intensities are Ff and Df for the YFP filter set and the CFP filter set the cross-talk corrected emission, intensities can be calculated by:

Ff-(Fd/Dd)Dfand Df-(Da/Fa)Ff
2.8

resulting in the following equation:

FfaDfd=Ff-(Fd/Dd)DfDf-(Da/Fa)Ff
2.9

and with the condition of Equation 2.6 and Equation 2.7 we gained:

FfaDfd=Ff-Df·0.63Df
2.10

One has to be aware that, although this measure of FRET is corrected for cross talk, it will not separate FRET and non-FRET signals. Consequently, it can not be used to analyze absolute values of FRET and absolute values of cAMP concentration, but it can be used to describe time-dependent changes.

Experimental System for cAMP Analysis by Using Epac1 Sensor

Light Sources

The main aspect of a suitable light source for donor excitation is an adequate light intensity. On the one hand, the intensity needs to be strong enough. This depends on the concentration of the fluorophores and the sensitivity of the camera, which limits the exposure time and frame rate, respectively. It must be assured that enough photons are collected during the exposure time by the CCD chip in order to receive a respectable signal-to-noise ratio. On the other hand, high light intensity results in bleaching of the fluorophores and even destruction of the specimen. Another important aspect of the light source is its spectrum. In order to gain a maximum of light intensity, it is useful to choose a light source which possesses a high intensity at the wavelength needed. This guarantees having less autofluorescence and a high signal-to-noise ratio. The highest intensity at a certain wavelength would give a laser or a high efficient LED. A xenon lamp emits its light through a wide range of wavelengths (~400–800 nm) with a more or less same intensity, whereas the emission of a mercury lamp will show several intensity bands along its spectrum. One of the mercury bands is at 435 nm, which makes mercury lamps reasonable for exiting the fluorophore CFP but not for GFP, because no band is present at 488 nm. For a xenon of mercury lamps one needs to select the bandwidth of wavelengths for excitation. This can be realized by using a monochromator, or much easier, with optical filters. We use a very light-sensitive camera with an EMCCD chip (iXon, Andor), allowing use of a 100 W xenon lamp connected to a monochromator (Optoscan, Kinetic Imaging) and light fiber (Figure 2.5).

FIGURE 2.5. Pathway of excitation as well as emission light through the setup is shown schematically.

FIGURE 2.5

Pathway of excitation as well as emission light through the setup is shown schematically. Excitation light originating from a monochromator enters the wide-field microscope through a light fiber. It is reflected by a dichotic mirror (DM) into the objective (more...)

Because the FRET efficiency is calculated by a ratio analysis, an inhomogeneous illumination of the specimen will not disturb the measurements as long as the inhomogeneity will not change during the time.

Optics

A high numeric aperture of the objective is needed in order to gain a high light intensity. We used an epifluorescent (reflected light) microscope, where the excitation light as well as the emitting light passes the same objective (Figure 2.5). In this case, the intensity of the detected light is proportional to the fourth power of numerical aperture (Inoué, 1986). It is recommended to use the whole area of the camera chip to obtain the highest possible resolution of the camera. The objective should magnify the image of the relevant cell or cell area to half of the area of the chip. We used a water immersion objective from Olympus (LUMFI) with 40× magnification and NA = 1.1.

The excitation light for CFP was filtered at 436/20 nm. Because we used an epifluorescent microscope, the excitation light had to be reflected with a 455 nm dichroic mirror into the objective pathway in order to excite the specimen (Figure 2.5). The 455 nm dichroic mirror passes the emission light of CFP and YFP collected by the objective to an image splitter. This image splitter represents the heart of the FRET setup, and it is placed between the microscope and the camera. It allows capturing two pictures simultaneously by using a single camera. A set of dichroic filters and mirrors splits the emitted and collimated light from the specimen in two spectrally separated light channels (Figure 2.5). Both channels are equipped with different filters. This results in a formation of two spatially identical but spectrally different images of the specimen on the camera (each image is positioned such that it uses one half of the CCD total area). Because we are analyzing FRET between CFP and YFP, we chose a 470/30 nm filter for the CFP channel, a 535/30 nm filter for the YFP channel and 515 nm for the dichroic mirror. In an ensuing image processing for further analysis, the two pictures have to be overlaid exactly, pixel over pixel. Therefore, it is very important to accurately adjust the two images on the CCD chip using micro-grids provided by the manufacturer.

Camera

Sensitivity, speed, and number of pixels are major parameters necessary for FRET experiments. The camera sensitivity will mainly influence the time resolution of the system. Higher light sensitivity allows shortening exposure time, resulting in a higher frame rate. However, the frame rate is limited due to relative slow translocation of charge into read-out areas of the CCD chip. We used the iXon camera from AndorTechnology with an electron-multiplying CCD chip (EMCCD) having a maximal frame rate of 34 Hz. By using this camera, we were able to work with exposure times of 100 msec and less with a good signal-to-noise ratio. Even if fast frame rates are not necessary for the experiment, one should consider using shorter exposure times with longer delays between two frames because this would reduce bleaching effects of the samples.

The spatial resolution of the image is determined not only by the number of pixels on the chip but also by the optical resolution of the microscope. The intensity resolution, however, is determined by the bit depth of each pixel. The CCD chip in the iXon camera we used consisted of 512 × 512 pixels. Each pixel had a bit depth of 14 bit. Thus, signals are digitalized using up to 16,384 gray scale levels, which give a dynamic range of 84 dB.

Examples

In the experiments described next we used an Epac sensor and FRET analysis to examine effect of serotonin receptors on intracellular cAMP level. For that, neuroblastoma glioma cells N1E-115 were transfected with the Epac construct and the serotonin receptor 5-HT7, which is known to activate the adenylyl cyclase (AC) via Gs-protein upon stimulation with an agonist. The measurement consisted in a series of 400 images taken with a frame rate of 1/sec. In order to prevent strong bleaching of the fluorophores by excitation, light exposure time was preferably short. We found we could still have a good signal-to-noise ratio using 100 msec as an exposure time. For the rest of the 900 msec excitation light was turned off by a shutter. After 200 msec, the cells were treated with 5-carboxamidotryptamine (5-CT), which is a selective 5-HT7 receptor agonist. An agonist was applied with an inline solution application MPRE8 from Cell Micro Controls directly on top of the respective cell, which allows a solution exchange in few seconds. The disadvantage of the inline solution application system MPRE8 is that it is vulnerable to have air bubbles emitted from the opening. The example of such an artifact produced by the air bubble is shown in Figure 2.6. It is important to note that this artifact will not appear in the analysis of the CFP to YFP ratio, which proves the analysis to be insensitive towards non-FRET-related intensity fluctuations. From the monochromic series of images, a two-color series was created by the IQ-program. From each image one half-image (Figure 2.7, left) was overlapped with the other half-image (Figure 2.7, right). The two colors of the series represented the emission light of the two channels of the image splitter.

FIGURE 2.6. FRET analysis results from the experiments introduced in this chapter.

FIGURE 2.6

FRET analysis results from the experiments introduced in this chapter. CFP and YFP intensities were measured from a neuroblastoma cell N1E-115 transfected with Epac and 5-HT7 receptor. (A) Region of interest (blue) drawn around the cell as well as the (more...)

FIGURE 2.7. Half-images originating from the same specimen.

FIGURE 2.7

Half-images originating from the same specimen. The left side represents the CPF channel and the right side does the YFP channel from the image splitter. The image shown is one of a whole image series taken during the experiment introduced in this chapter. (more...)

An area of interest was defined covering the cell and from the mean intensity of this area, the background intensity was subtracted. The background intensity was gained from the region of interest beside the cell. The intensity traces resulting from the subtraction represent the variables Ff and Df, respectively, from Equation 2.8. Using this equation we calculated the cross talk corrected intensity Ffcorr from the YFP channel:

Ffcorr=Ff-Df·0.63
2.11

Compared to Equation 2.10 we did additional normalization of the traces shown in Figure 2.6 in order to receive a ratio value of one before the agonist application. The traces were normalized to the value 0 at 50 msec:

Ffnormcorr=Ffcorr(t)Ffcorr(50ms)and Dfnorm=Df(t)Df(50ms)
2.12

The equation for the ration trace, which is inversely proportional to FRET, has therefore following form related to Equation 2.10:

(FfaDfd)norm=FfnormcorrDfnorm
2.13

It has to be mentioned that non-FRET signals are still included in the normalized FRET signal. Therefore, it is questionable to compare normalized CFP to YFP ration as readout for FRET from different cells with the intention to compare amplitudes. But nothing argues against a comparison of time-depended characteristics. With respect to this argumentation, a high accuracy in selecting the area of interest is needless as long as no other cells are located in close proximity.

Outlook

So far we have discussed the relative changes of the FRET signal only. With this technique it is hardly possible to compare measurements between individual cells and to acquire the absolute values of cAMP concentration. A more quantitative analysis strategy has been recently proposed by Hoppe and colleagues (Hoppe et al., 2002). In this work, a stoichiometric method is described that uses two excitation wavelengths and three filter sets to measure the FRET efficiency and the relative concentrations of donor and acceptor, as well as the fractions of donor and acceptor in complex. The fluorescence images obtained with the filter sets are FexD, emD with the donor filter set, FexA, emA with the acceptor filter set, and FexD, emA with the FRET filter set, where the subscriptions exD/A stand for the excitation wavelength for donor and acceptor, respectively, and the subscriptions emD/A stand for the emission wavelength range for donor and acceptor, respectively. The filter sets must be chosen so that (1) no acceptor emission is detected at the donor emission wavelength FexD,emDA, = 0, and (2) no donor excitation occurs at the acceptor excitation wavelength FexA,emAD = 0. Using the theory derived by Lacowicz (Lakowicz, 1999) and taking into account the bleed through or the “cross talk” of the donor emission to the acceptor emission band and the acceptor emission excited at the donor excitation wavelength, the characteristic efficiency of energy transfer can be calculated by the following equation:

EC=γ(FexD,emA-βFexD,emDDA-αFexA,emAADαFexA,emAAD)1fAwith α=FexD,emAAFexA,emAA=ɛexDAɛexAA,β=FexD,emADFexD,emDDand γ=ɛexDAɛexDA.
2.14

where fA is the fractional labeling of the acceptor with donor or the fraction of acceptor in complex with the donor. The correction terms α and β can be obtained by separate calibration measurements using acceptor only with the FRET and the acceptor filter sets, and using donor only with the FRET and the donor filter sets. γ could be calculated from literature values. If EC is known, fA can be directly obtained by the use of the three filter sets.

fA=[DA][Atot]=γ(FexD,emADA-βFexD,emDDA-αFexA,emADAαFexA,emADA)1EC
2.15

If the extinction coefficients of the donor and acceptor at the donor excitation wavelength are not available, γ can be obtained by a tandem construct where fA is equal to one. However, in both cases EC must be acquired in a separate measurement.

If EC can not be obtained, an apparent efficiency EA of transfer to the acceptor

EA=ECfA=γ(FexD,emA-βFexD,emDDA-αFexA,emAADαFexA,emAAD)
2.16

can be discussed. This efficiency is still quantitative in that changes in EA reflect real changes in the number of acceptor-labeled molecules in complex.

By using this strategy, the absolute measure of the cAMP concentration is possible after calibration of cAMP concentration as a function of fA. Due to its quantitative nature, this strategy also allows a comparison between individual experiments. In this way the specimen can be investigated under physiological conditions at a sufficient time resolution.

Acknowledgments

We thank Dr. Kees Jalink from the Department of Cellular Biophysics, The Netherlands Cancer Institute, who kindly provided us with cDNA encoding for the CFP-Epac-YFP fusion construct. This work was supported by the Deutsche Fors-chungsgemeinschaft through the Centre of Molecular Physiology of the Brain and Grant PO 732/1-2 to E.G.P. Additional support was provided by grants from the American Heart Association to TVY. TVY is an “Established Investigator” of the American Heart Association.

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