Use of Fluorescence Resonance Energy Transfer-based Biosensors for the Quantitative Analysis of Inositol 1,4,5-Trisphosphate Dynamics in Calcium Oscillations^,

Abstract

Inositol 1,4,5-trisphosphate (IP₃) is an intracellular messenger that elicits a wide range of spatial and temporal Ca²⁺ signals, and this signaling versatility is exploited to regulate diverse cellular responses. In this study, we have developed a series of IP₃ biosensors that exhibit strong pH stability and varying affinities for IP₃, as well as a method for the quantitative measurement of cytosolic concentrations of IP₃ ([IP₃]_i) in single living cells. We applied this method to elucidate IP₃ dynamics during agonist-induced Ca²⁺ oscillations, and we demonstrated cell type-dependent differences in IP₃ dynamics, a nonfluctuating rise in [IP₃]_i and repetitive IP₃ spikes during Ca²⁺ oscillations in COS-7 cells and HSY-EA1 cells, respectively. The size of the IP₃ spikes in HSY-EA1 cells varied from 10 to 100 nm, and the [IP₃]_i spike peak was preceded by a Ca²⁺ spike peak. These results suggest that repetitive IP₃ spikes in HSY-EA1 cells are passive reflections of Ca²⁺ oscillations, and are unlikely to be essential for driving Ca²⁺ oscillations. In addition, the interspike periods of Ca²⁺ oscillations that occurred during the slow rise in [IP₃]_i were not shortened by the rise in [IP₃]_i, indicating that IP₃-dependent and -independent mechanisms may regulate the frequency of Ca²⁺ oscillations. The novel method described herein as well as the quantitative information obtained by using this method should provide a valuable and sound basis for future studies on the spatial and temporal regulations of IP₃ and Ca²⁺.

Inositol 1,4,5-trisphosphate (IP₃)2 is an important intracellular messenger produced by phospholipase C (PLC)-dependent hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP₂). IP₃ releases Ca²⁺ from intracellular stores via IP₃ receptors (IP₃Rs), and the resulting Ca²⁺ signals often exhibit complex spatial and temporal organizations, such as Ca²⁺ oscillations (1). The mechanism responsible for Ca²⁺ oscillations has been a long-standing question, and a number of experimental approaches and mathematical models have been reported to account for these Ca²⁺ signals, yet the mechanism responsible remains controversial (2). There are two general classes of Ca²⁺ oscillation models (3). In one class, Ca²⁺ oscillations are generated in the presence of constant cytosolic IP₃ concentrations ([IP₃]_i) (4); in the other class, oscillating [IP₃]_i are required to drive Ca²⁺ oscillations (5). The physiological relevance of the former class has been supported experimentally by using nonmetabolizable IP₃ analogs (6), and by the observation of repetitive Ca²⁺ release in permeabilized cells with clamped IP₃ concentrations (7, 8). On the other hand, oscillatory changes in [IP₃]_i have been suggested by the observed cyclical translocation of a GFP-tagged pleckstrin homology domain of PLC-δ (GFP-PHD) (9, 10). However, in other experiments using more specific IP₃ biosensors, IP₃ was shown to accumulate gradually with little or no fluctuation during Ca²⁺ oscillations (11). These discrepant observations may be attributable to differences between various IP₃ biosensors and a lack of quantitation.

There are two types of IP₃ biosensors, GFP-PHD and IP₃R-based FRET sensors. GFP-PHD binds to both PIP₂ and IP₃; thus it has been thought that changes in [IP₃]_i could be monitored indirectly by the release of membrane-bound GFP-PHD (9). IP₃R-based FRET biosensors consist of the ligand-binding domain of IP₃R and a pair of fluorescent proteins, cyan fluorescent protein and yellow fluorescent protein. Since the successful monitoring of IP₃ with LIBRA (12), the first IP₃R-based FRET biosensor, several different groups have used similar biosensors for IP₃ monitoring (11, 13, 14). In principle, quantitative measurements of [IP₃]_i are not possible with GFP-PHD. In addition, it is recognized that GFP-PHD may be released from the plasma membrane by decreases in available PIP₂ (15), which could be attributed to PIP₂ hydrolysis or the occupation by other molecules. IP₃R-based FRET biosensors offer significant benefits for monitoring IP₃ based on their high selectivity for IP₃ and ratiometric measurement.

In this study, we developed a series of improved IP₃ biosensors that exhibit high pH stability and varying IP₃ affinities. They also possess higher selectively and afford a larger dynamic range than that of original LIBRA. In combination with these new biosensors, we developed a method for quantitating IP₃ dynamics in single living cells, and we applied this method to measure IP₃ dynamics during Ca²⁺ oscillations.

EXPERIMENTAL PROCEDURES

Media—Hanks' balanced salt solution with Hepes (HBSS-H) contained 137 mm NaCl, 5.4 mm KCl, 1.3 mm CaCl₂, 0.41 mm MgSO₄, 0.49 mm MgCl₂, 0.34 mm Na₂HPO₄, 0.44 mm KH₂PO₄, 5.5 mm glucose, 20 mm Hepes-NaOH (pH 7.4). Intracellular-like medium (ICM) contained 125 mm KCl, 19 mm NaCl, 10 mm Hepes-KOH (pH 7.3), 1 mm EGTA, and 330 μm CaCl₂ (for 50 nm free Ca²⁺).

Plasmid Construction—Venus, EYFP with F46L, F64L, M153T, V163A, and S175G, was constructed using site-directed mutagenesis of pEYFP-N1 (Clontech) and a QuikChange® II XL site-directed mutagenesis kit (Stratagene, La Jolla, CA), according to the manufacturer's instructions. Primers 1-6 were used for mutagenesis (all primers used in this study are listed in supplemental Table S1). The sequence of the Venus construct (pVenus-N1) was verified by DNA sequencing.

To construct pH-stable LIBRA (LIBRAvIII), the portion of LIBRA containing the membrane-targeting signal, enhanced cyan fluorescent protein, the IP₃-binding domain of the rat type 3IP₃R (amino acids 1-604), and NheI and EcoRI sites at either end was amplified by PCR using primers 7 and 8 and LIBRA plasmid as the template. This PCR product was then ligated into the NheI and EcoRI sites of pVenus-N1.

To construct LIBRA variants with type 1 IP₃R (LIBRAvI), the IP₃-binding domain of the rat type 1 IP₃R (amino acids 1-604) with XhoI sites incorporated at both ends was amplified by PCR using primers 9 and 10 and a rat brain cDNA library as the template. This PCR product was then ligated into the linker region XhoI site in the LIBRAvIII plasmid. In a similar way, we constructed LIBRAvII with the IP₃-binding domain of the rat type 2 IP₃R (amino acids 1-604) using primers 11 and 12 and a rat parotid cDNA library as the template. The high affinity variant of LIBRAvIII (LIBRAvIII with mutation R440Q; LIBRA-vIIIS) was prepared by site-directed mutagenesis of the ligand-binding domain of LIBRAvIII using primers 13 and 14. In a similar way, the high affinity variant of LIBRAvII (LIBRAvIIS) was prepared by site-directed mutagenesis of LIBRAvII using primers 15 and 16. Some PCR errors were identified within the IP₃-binding domain of LIBRAvI, LIBRAvII, and LIBRAvIIS. Nucleotide sequences of these constructs were corrected by site-directed mutagenesis, and the corrected sequences were confirmed by DNA sequencing.

We previously constructed an IP₃-insensitive mutant (K507A) of LIBRA, which we referred to as LIBRA-N. The IP₃-insensitive variant of LIBRAv (LIBRAvN) was constructed by cutting the mutated IP₃-binding domain of LIBRA-N-plasmid with XhoI and ligating the fragment into LIBRAvIII-plasmid cut with the same enzyme.

Cell Culture and Transfection—COS-7 cells, obtained from RIKEN Cell Bank (Tokyo, Japan), were cultured in Dulbecco's modified Eagle's medium with low glucose (1000 mg/liter), supplemented with 10% fetal calf serum, 584 mg/liter l-glutamine, 110 mg/liter sodium pyruvate, 100 units/ml penicillin, and 100 μg/ml streptomycin (all from Invitrogen). HSY-EA1 cell was subcloned from HSY human parotid cell line, a generous gift from Dr. Mitsunobu Sato (Tokushima University, Japan), by a dilution plating technique. HSY-EA1 cells were cultured in Dulbecco's Eagle's medium nutrient mixture Ham's F-12 (Sigma) supplemented with 10% newborn calf serum, 2 mm glutamine, 100 units/ml penicillin, and 100 μg/ml streptomycin, as described previously. These cells were grown in fibronectin-coated experimental chambers consisting of plastic cylinders (7 mm in diameter) glued to round glass coverslips.

Measurement of Fluorescence—Cells were washed with HBSS-H and rested for at least 5 min prior to experiments. In some experiments, cells were incubated at room temperature for 1-2 min in HBSS-H containing 2.5 μm fura-2 acetoxymethyl ester (Dojin Chemicals, Kumamoto, Japan). Permeabilization was performed by applying ICM containing 100 μg/ml (w/v) saponin (ICN, Cleveland, OH) for 1-1.5 min. In some experiments, cells were permeabilized with ICM containing 200 μm β-escin (Sigma). Fluorescence images were captured using a dual wavelength ratio imaging system (Hamamatsu photonics, Shizuoka, Japan) consisting of a C9100-13 EM-CCD camera and W-View optics coupled to a Nikon TE2000 inverted fluorescence microscope equipped with a Nikon S Fluor 60 oil immersion objective (NA 1.3). Fluorescence of IP₃ biosensors was monitored with excitation at 425 nm and dual emission at 480 and 535 nm. Fluorescence of fura-2 was monitored with sequential excitation at 345 and 380 nm and emission at 535 nm. AQUACOSMOS 2.6 software (Hamamatsu Photonics) and ImageJ program were used for image analyses. To minimize the effect of photobleaching on the estimation of [IP₃]_i, time-dependent decreases in the fluorescence intensities at two emission wavelengths (480 and 535 nm) were monitored for 5-10 min prior to the stimulations, and the photobleaching rates were calculated by fitting the data to linear or exponential equations.

Determinations of K_d and Hill Coefficient—Data were analyzed by simulated annealing procedure with GOSA-fit software (BIO-LOG, Toulouse, France) to fit the data to Equation 1,

(Eq.1)

where C is the IP₃ concentration; E_max is the maximal effect (100%), and n is the Hill coefficient.

Estimation of [IP₃]_i—To estimate resting [IP₃]_i, emission ratios of LIBRAvIIS in intact cells before (R_rest) and after (R_min) treatment with U73122, and emission ratios in the absence (R_min′) and presence (R_max′) of saturating concentrations of IP₃ were monitored after permeabilization. [IP₃]_i can be calculated by Equation 2,

(Eq.2)

where ΔR is R_rest - R_min; ΔR_max is (R_max′-R_min′) R_min R_min′^-1; K_d is the apparent dissociation constant, and n is the Hill coefficient. Because the variability of resting [IP₃]_i was reasonably small, we used averaged resting [IP₃]_i to determine R_min by Equation 3,

(Eq.3)

where E_rest is the E (% max) of resting [IP₃]_i, which is given by Equation 1. [IP₃]_i was then calculated using Equation 2.

Determinations of Response Rate—LIBRAvIIS-expressing COS-7 cells were permeabilized with saponin, and changes in emission ratio were monitored with the first acquisition protocol (20-50 ms/frame). The response rate for the IP₃-dependent increase in ratio was examined by application of 10 μm IP₃ to the experimental chamber containing saponin-treated LIBRA-vIIS-expressing cells. To examine the rate of decrease in ratio due to the removal of IP₃, permeabilized LIBRAvIIS-expressing cells were initially exposed to 1 μm IP₃, and subsequently washed out using IP₃-free ICM. In this experimental condition, ∼70% of medium was replaced by a single wash. Using a non-linear least squares method, these data were fitted by the equation derived from a solution of the chemical reaction model, Equation 4,

(Eq.4)

where R₀ is the emission ratio at time 0 (the time when the medium in the chamber was replaced); t is the time after the replacement of the medium; R_t is the emission ratio at time t; and A, C, and γ are arbitrary constants. This equation yields the time for the half-maximal increase or decrease in ratio as t_½ = γ^-1 ln(2 - C^-1). Note that this model is based on the assumption that medium (ICM with or without IP₃) within the permeabilized cell is replaced completely at t = 0, whereas the actual time for the replacement is later than at t = 0. It is therefore expected that actual t_½ values are at least less than those calculated with this method. See details in the supplemental material.

RESULTS AND DISCUSSION

Characterization of Improved IP₃ Biosensors—Fig. 1A shows schematic diagrams of IP₃ biosensor domain structures. To improve the pH stability of the LIBRA emission ratio (480/535 nm), EYFP was replaced with Venus, a pH-stable yellow fluorescent protein mutant (16). The resulting construct (LIBRAvIII) showed strong pH stability in the range of pH 6-8 (Fig. 1B). Next the LIBRAvIII ligand-binding domain was replaced with that of type 1 or type 2 IP₃R, to create high affinity IP₃ biosensors. These constructs were designated LIBRAvI and LIBRAvII, respectively. It is known that changing Arg to Gln at position 441 (R441Q) increases the affinity of type 1 IP₃R (17). To further increase the affinity, comparable amino acid substitutions in type 2 and type 3 IP₃Rs (R440Q) (18) were made in LIBRAvII and LIBRAvIII. We also generated IP₃-insensitive LIBRAv (LIBRAvN) by substituting Ala for Lys at position 508 (K508A) in the IP₃-binding domain of LIBRAvIII. These biosensors were distributed on the plasma membrane and in vesicular structures (Fig. 1C), and most of the associated fluorescence (>90%) was retained after permeabilization.

FIGURE 1.

Characteristics of IP₃ biosensors. A, schematic representations of domain structures of LIBRA and LIBRAv variants. IP₃ biosensors consist of a membrane-targeting signal (GAP43); the ligand-binding domain of rat IP₃R types 1, 2, or 3 (amino acids 1-604); enhanced cyan fluorescent protein, EYFP, or Venus; and linkers (L1 and L2). K507A and R440Q denote amino acids substitutions of the ligand-binding domain of the IP₃R types 2 and 3. B, effects of pH on fluorescence emission ratios of LIBRA and LIBRAvIII. Emission ratios (480 nm/535 nm) of LIBRA and LIBRAvIII in permeabilized COS-7 cells were measured in ICM at various pH values. Emission ratios were normalized to the ratio at pH 7.3. C, fluorescent images of LIBRAvIIS-expressing COS-7 cells before and after permeabilization. D, concentration-response curves for inositol phosphates. Changes in emission ratio of LIBRAv variants because of exposure to various concentrations of IP₃ (circle), IP₂ (triangle), and IP₄ (square) were measured in permeabilized COS-7 cells (LIBRAvIII, LIBRAvII, and LIBRAvIIS) or in permeabilized HSY-EA1 cells (LIBRAvI). Changes in emission ratio were normalized to the effects of IP₃ saturation with 10 μm (for LIBRAvI, -II, and -IIS) or 30 μm (for LIBRAvIII) IP₃.

To quickly characterize these new candidate biosensors, we examined changes in emission ratios in permeabilized cells in response to stepwise increases in IP₃ concentration (supplemental Fig. S1). The results of this preliminary characterization indicated that the apparent affinities were LIBRA ≈ LIBRAvIII < LIBRAvIIIS ≈ LIBRAvI ≈ LIBRAvII < LIBRAvIIS, and the extent of maximal changes in the emission ratios of LIBRAvIII, LIBRAvIIIS, LIBRAvII, and LIBRAvIIS were ∼2-fold larger than that of LIBRA. We also noticed that LIBRAvI worked well in HSY-EA1 cells (supplemental Fig. S1G) but not in COS-7 cells (supplemental Fig. S1D).

Concentration-response curves of the new IP₃ biosensors for IP₃, inositol 4,5-bisphosphate (IP₂), and inositol 1,3,4,5-tetrakisphosphate (IP₄) are shown in Fig. 1D. The apparent K_d values of LIBRAvIII, LIBRAvI, LIBRAvII, and LIBRAvIIS for IP₃ were 491.5, 268.7, 233.6, and 117.2 nm, respectively. A high concentration (10 μm) of IP₂ or IP₄ induced 20-40% of the maximal response of these biosensors, and the estimated K_d values of LIBRAvIII, LIBRAvII, and LIBRAvIIS for IP₂ and IP₄ were estimated (supplemental Table S2). LIBRAvII and LIBRAvIIS exhibited greater selectivity than LIBRA, and the selectivity of LIBRAvIIS for IP₃ was 300-fold higher than for IP₂ and 96-fold higher than for IP₄.

The characteristics of our IP₃ biosensors include the use of Venus, ligand-binding domains of different IP₃R isoforms, and a membrane-targeting signal. The superior selectivity of IP₃R-based FRET sensors provides a clear advantage over GFP-PHD sensors. In addition, utilizing Venus for a FRET-based biosensor is particularly important to avoid pH-related artifacts (16, 19).

The ligand-binding domain of IP₃Rs is composed of two functional domains, the amino-terminal suppressor domain and the carboxyl-terminal IP₃-binding core domain (17). Unlike other IP₃R-based FRET sensors (11, 13), LIBRA and LIBRAv variants contain both IP₃ suppressor and core domains. Because the molecular properties of IP₃R isoforms have been studied extensively, it is relatively easy to construct biosensors with appropriate levels of affinity. In addition, it has been reported that structural differences in the suppressor domains contribute to functional diversity in ligand sensitivity among IP₃R isoforms (20), assuming that the ligand-binding properties of the LIBRAv series reflect this feature of IP₃R isoforms. We previously reported a method using LIBRA for determining IP₃R ligands (21), and we identified novel ligands of IP₃Rs from newly synthesized cyclopentane derivatives (22). This method could be extended easily for identifying subtype-specific ligands of IP₃Rs by using a series of new LIBRAv variants.

Imaging of IP₃-dependent Response of LIBRAvIIS—Emission ratios within an individual cell, whether intact or permeabilized, were uneven, whereas the magnitudes of the maximal change in ratio in response to 10 μm IP₃ were reasonably consistent (supplemental Fig. S2). Therefore, we visualized IP₃-dependent changes in the fluorescence emission ratio with normalized ratio images (Fig. 2A), where each ratio image was divided by an image before the application of IP₃. The normalized LIBRAvIIS emission ratio increased homogeneously except for the area including intracellular vesicles in cell 2 (Fig. 2B). It was noticed that abundant accumulation of IP₃ sensors on intracellular vesicles tended to decrease the extent of IP₃-dependent changes in the emission ratio. We then applied this procedure to visualize the ATP-induced increase in LIBRAvIIS emission ratio and subsequent decrease because of the removal of ATP in intact COS-7 cells (Fig. 2, C and D).

FIGURE 2.

Image analysis of LIBRAvIIS fluorescence in permeabilized and intact cells. Permeabilized (A and B) and intact COS-7 cells (C and D) were exposed to 10 μm IP₃ and 10 μm ATP, respectively. A and C, F0, fluorescence image; R/R₀ 1-5, images of normalized emission ratio. Ratio images were normalized by the ratio image at time point 0 in B or D. B and D, IP₃-induced changes in normalized emission ratios. IP₃ or ATP was applied and washed out at the times indicated by the arrowheads in B or D. Numbers in B and D correspond to the numbers on each image in A and C, respectively. Thin colored lines in B and D are normalized ratios in areas shown by same color in the fluorescence images (F0), and thick black lines are values of each cells.

Response rates of IP₃ biosensors were examined by high speed monitoring of IP₃-dependent changes in the emission ratio of LIBRAvIIS in permeabilized cells and a least squares curve-fitting technique. The emission ratio increased to the half-maximal level in ∼100 ms following the application of 10 μm IP₃. The estimated time for the half-maximal increase (t_½on) and decrease (t_½off) in the emission ratio was 162 and 169 ms, respectively (supplemental Fig. S3). These analyses indicate that the response rate of LIBRAvIIS is sufficiently rapid to reflect responses that occur ∼100 ms or longer. However, the spatial resolution and signal to noise ratio necessary to detect subcellular difference in the high speed monitoring of IP₃ were not achieved in our experimental system.

Inclusion of a membrane-targeting signal provided a rapid means for examining biosensors expressed in permeabilized cells (supplemental Fig. S1) and enabled calibration of FRET signals in single cells (Fig. 3). However, nonuniform distributions of biosensors caused a subcellular variability in the ratio. This variability was overcome by using normalized emission ratio images, although this method is not suitable for measurements in motile cells. Further improvement of IP₃ biosensor dynamic ranges is required for the high speed monitoring of subcellular IP₃ responses.

FIGURE 3.

Quantitative analysis of changes in fluorescence ratio of LIBRAvIII and LIBRAvIIS. COS-7 cells expressing either LIBRAvIII (A) or LIBRAvIIS (B) were treated with 10 μm ATP and subsequently with 5 μm U73122. To obtain the maximal change in emission ratio, cells were washed with ICM, permeabilized with saponin (Sap) (100 μg/ml), and exposed to saturating concentrations of IP₃ (10 or 30 μm). Effects of 10 μm ATP and U73122 depicted in A and B are shown as % max in C and D, respectively. Effects of U73133 (5 μm) and U73122 (5 μm) on emission ratios of LIBRAvIII (E) and LIBRAvIIS (F) in intact unstimulated cells are shown.

Methods for Quantitative Measurement of [IP₃]_i—Emission ratios of LIBRAvIII and LIBRAvIIS in intact cells increased upon the application of 10 μm ATP, and returned to basal levels after the addition of 5 μm U73122 (Fig. 3). These reagents did not change the emission ratio of LIBRAvN (data not shown). To obtain the maximal changes in emission ratio (ΔR_max) in each individual cell, cells were permeabilized and exposed to IP₃ following the completion of measurements in intact cells (Fig. 3, A and B). Biosensor-expressing cells and LIBRAvN-expressing cells showed decreases in their fluorescence ratios upon permeabilization. These changes in fluorescence are thought to be due to effects on the fluorescent proteins rather than to effects on the IP₃-binding domain, and thus they are unlikely to interfere with IP₃-dependent changes in emission ratios.

In Fig. 3, C and D, changes in emission ratios are quantitatively shown as % of maximal change in ratio (% max). The difference in % max values of ATP-induced changes in emission ratios between LIBRAvIII and LIBRAvIIS is thought to reflect the difference in affinities of these IP₃ sensors. We further examined resting [IP₃]_i by treating unstimulated cells with U73122. The LIBRAvIII emission ratio did not change with U73122 treatment (Fig. 3E), whereas the LIBRAvIIS ratio decreased slowly to a new steady state (Fig. 3F). These results indicate that the emission ratio of LIBRAvIIS reflects the resting [IP₃]_i, and U73122 decreases [IP₃]_i to levels below the detectable range of LIBRAvIIS. Consistent with this interpretation, Sato et al. (13) reported that U73122-induced decreases in the emission ratio of intact cells were observed using a high affinity IP₃ biosensor. Based on this idea, we used the U73122-induced decrease in emission ratios, K_d, and Hill coefficient of LIBRAvIIS (shown in Fig. 1D) to estimate the resting [IP₃]_i in COS-7 and HSY-EA1 cells. U73122-induced decrease in emission ratio of LIBRAvIIS in COS-7 and HSY-EA1 cells was 13.67 ± 0.96 (mean ± S.E., n = 60) and 16.03 ± 1.53 (n = 19), respectively. The estimated resting [IP₃]_i in COS-7 and HSY-EA1 cells was 15.09 ± 1.38 and 18.16 ± 2.49 nm, respectively. Resting [IP₃]_i values allowed us to accurately calculate agonist-induced changes in [IP₃]_i. In calculations for LIBRAvIIS, omitting adjustment for resting [IP₃]_i caused a noticeable underestimation in concentration (Fig. 4D), whereas the effects of adjusting calculations for resting [IP₃]_i was limited for LIBRAvIII (Fig. 4C). In addition, the impact of basal noise of the LIBRAvIIS fluorescence on the basal level of calculated [IP₃]_i was negligible (Fig. 4D, arrowhead), indicating that LIBRAvIIS is suitable for monitoring small increases in [IP₃]_i up to 200 nm. Changes in the emission ratio of LIBRAvIII corresponded well over a broad range of [IP₃]_i, up to ∼400 nm, whereas base-line value fluctuations near the resting [IP₃]_i produced a noticeable difference in the estimated [IP₃]_i (Fig. 4C, arrowheads). These results indicate that LIBRAvIII is convenient for monitoring broad ranges of [IP₃]_i.

FIGURE 4.

Estimation of [lsqb]IP₃]_i with LIBRAvIII and LIBRAvIIS. ATP-induced changes in emission ratios of LIBRAvIII (A) and LIBRAvIIS (B) in intact COS-7 cells are shown. These % max values were converted to [IP₃]_i in C and D, with (solid lines) or without (dashed lines) adjustment for the resting [IP₃]_i.

In this study, [IP₃]_i was estimated under the following assumptions: 1) that the properties of IP₃ biosensors in permeabilized cells are comparable with those in intact cells, and 2) that U73122 reduces [IP₃]_i below the detectable level of the biosensors. To examine possible effects of cytosolic proteins on biosensor response, we compared IP₃-induced changes in the ratios of LIBRAvIIS in β-escin-permeabilized cells and in saponin-permeabilized cells and found comparable IP₃-induced responses (supplemental Fig. S4). β-Escin-permeabilized cells have been used to examine the functions of cytosolic proteins,3 whereas cytosolic proteins are lost in saponin-permeabilized cells (7, 23). Thus, the effects of endogenous cytosolic proteins on the IP₃-induced response of biosensors could be ruled out. In addition, our previous study indicates that IP₃-dependent changes in the ratio of LIBRA are not altered by Ca²⁺ or ATP, and that the effect of pH on fluorescent proteins does not alter the IP₃-dependent changes in the fluorescence of LIBRA (12). Although these experiments do not exclude possible effects of other small endogenous molecules, it is reasonable to assume at this stage that IP₃-dependent changes in the ratios of these types of biosensors in permeabilized cells are comparable with those in intact cells.

We also examined the effects of U73122 on ATP-induced Ca²⁺ responses, and we found that the pretreatment of COS-7 cells with 5 μm U73122 completely blocked the rise in [Ca²⁺]_i obtained by 3 μm ATP, and strongly decreased responses obtained with 10 μm ATP (data not shown). It is therefore thought that U73122 pretreatment is sufficient to block the low level of PLC activity in unstimulated cells. Indeed, we have used this method to estimate the [IP₃]_i required to elicit Ca²⁺ responses (see below), and these values are reasonably close to the threshold concentration of photoreleased [IP₃]_i (60 nm) that triggers Ca²⁺ spikes in Xenopus oocytes (24).

Changes in [IP₃]_i during Agonist-induced Ca²⁺ Oscillations—The mechanism responsible for Ca²⁺ oscillations and the associated dynamics of IP₃ have been of long-standing interest (2). Experiments based on the translocation of GFP-PHD have suggested that [IP₃]_i oscillate (9, 10), whereas an IP₃R-based FRET biosensor has shown that IP₃ accumulates gradually in the cytosol with little or no fluctuation during Ca²⁺ oscillations (11). Because of conflicting data and a lack of quantitation of IP₃ dynamics, it remains controversial whether [IP₃]_i truly fluctuates and whether proposed [IP₃]_i fluctuations drive Ca²⁺ oscillations. To clarify these important questions, we quantitatively monitored IP₃ dynamics during Ca²⁺ oscillations using LIBRAvIIS.

The upper panels of Fig. 5, A-D, show changes in emission ratios of LIBRAvIIS and fura-2, and the lower panels indicate calculated [IP]_i during ATP-induced Ca²⁺ oscillations. In COS-7 cells, stimulation with either 1 or 3 μm ATP increased [IP₃]_i slowly to a sustained level without detectable fluctuations, and Ca²⁺ oscillations were observed during this increase and sustained elevation of [IP₃]_i (Fig. 5, A and B). Unlike ATP-induced increases in [Ca²⁺]_i, the large increase in [Ca²⁺]_i caused by ionomycin (2 μm) treatment had no effect on the emission ratio of LIBRAvIIS, indicating that Ca²⁺ itself does not activate IP₃ generation in COS-7 cells.

FIGURE 5.

IP₃ dynamics during Ca²⁺ oscillations in COS-7 and HSY-EA1 cells. LIBRAvIIS-expressing cells were loaded with fura-2 and sequentially stimulated with various concentrations of ATP. A and B, COS-7 cells showed no detectable fluctuation in [IP₃]_i during ATP-induced Ca²⁺ oscillations. Traces are representative of 27 oscillating cells. C and D, HSY-EA1 cells showed repetitive IP₃ spikes during ATP-induced Ca²⁺ oscillations. Traces are representative of 31 of 55 oscillating cells. Upper traces of each panel show emission ratios of LIBRAvIIS (black lines) and excitation ratios of fura-2 (red lines). Lower traces show estimated [IP₃]_i (black lines), excitation ratio of fura-2 (red lines), and interspike periods of Ca²⁺ oscillations (blue lines). E, there is no change in emission ratio of LIBRAvN during ATP-induced Ca²⁺ oscillations in HSY-EA1 cells. Concentrations of ATP (μm) are shown in each panel. Black arrowhead, peak of IP₃ spike; red arrowhead, peak of Ca²⁺ spike; Iono, 2 μm ionomycin.

We also examined IP₃ dynamics in HSY-EA1 cells. This cell line is characterized by long lasting Ca²⁺ oscillations in response to wide ranges of agonist concentrations (23, 25). In fact, 65% of HSY-EA1 cells (55 of 84 cells) exhibited Ca²⁺ oscillations following treatment with 3-100 μm ATP or 10-100 μm carbachol. Interestingly, 56% of Ca²⁺-oscillating HSY-EA1 cells (31 cells) showed associated fluctuations in LIBRAvIIS emission ratios (Fig. 5, C and D). Similar fluctuations in the LIBRAvIIS emission ratio were observed when IP₃ dynamics were examined in the absence of fura-2 loading (data not shown). In contrast, no change in emission ratio was observed during Ca²⁺ oscillations in LIBRAvN-expressing HSY-EA1 cells (Fig. 5E). These experiments exclude the possibility of resulting artifacts derived from IP₃-independent changes in LIBRAvIIS fluorescence and possible interference by fura-2 fluorescence. These results demonstrate cell type-specific differences in IP₃ dynamics, nonfluctuating rises in [IP₃]_i and repetitive IP₃ spikes in COS-7 cells and HSY-EA1 cells, respectively. Quantitative examinations revealed that repetitive IP₃ spikes in HSY-EA1 cells occurred concomitantly with a slow basal accumulation of [IP₃]_i. The size of IP₃ spikes varied from 10 to 100 nm, and the second and later spikes were initiated before the decline of [IP₃]_i to resting levels, resulting in a slow increase in the [IP₃]_i interspike.

It is generally thought that IP₃ diffuses rapidly within the cell, and thus we think that the fluorescence of membrane-bound biosensors reflects overall cytosolic [IP₃]_i. In agreement with this idea, we observed nonfluctuating IP₃ responses in COS-7 cells and repetitive IP₃ spikes in HSY-EA1 cells in both cytosolic and nuclear areas using a biosensor lacking the membrane targeting sequence.3

Although repetitive IP₃ spikes were observed in HSY-EA1 cells, our observations do not support the requirement of IP₃ fluctuations in Ca²⁺ oscillations. Although [IP₃]_i showed clear fluctuations at the beginning of Ca²⁺ oscillations, repetitive spikes of [IP₃]_i were gradually obscured during Ca²⁺ oscillations in 64% of HSY-EA1 cells. In addition, the [IP₃]_i spike peak was preceded by a Ca²⁺ spike peak (Fig. 5, C and D). These results suggest that repetitive IP₃ spikes in HSY-EA1 cells are passive reflections of the Ca²⁺ oscillations, and are unlikely to be essential for driving Ca²⁺ oscillations.

[IP₃]_i fluctuations could be induced by the effects of Ca²⁺ on IP₃ synthesis and/or IP₃ degradation. Applications of 2 μm ionomycin had little or no effect on the emission ratio of LIBRAvIIS in HSY-EA1 cells (Fig. 5C), suggesting that the direct effect of Ca²⁺ on IP₃ production is very small or absent in this cell line. Thus, [IP₃]_i fluctuations are likely to be caused by Ca²⁺-induced potentiation of agonist-dependent IP₃ generation. The IP₃ spikes described here resemble the pattern predicted by the oscillator model, in which positive feedback via Ca²⁺-dependent activation of PLC is added to the dual positive and negative feedback effect of Ca²⁺ on IP₃R, rather than the model including negative feedback via Ca²⁺-dependent IP₃ degradations by IP₃ 3-kinases (26).

Ca²⁺ oscillations were observed primarily when [IP₃]_i was less than 300 nm (Fig. 6, A and B). More than 50% of COS-7 cells exhibited Ca²⁺ oscillations when [IP₃]_i was 50-100 nm, and the percentage of oscillating COS-7 cells decreased as [IP₃]_i increased (Fig. 6C). In HSY-EA1 cells, Ca²⁺ oscillations were observed in 50-70% of cells, when interspike [IP₃]_i was less than 250 nm, and the percentage of oscillating cells decreased abruptly (11.1%) when interspike [IP₃]_i was greater than 250 nm (Fig. 6D). These results indicate that low concentrations of IP₃ (<100 nm) induce Ca²⁺ oscillations in both cell types, whereas HSY-EA1 cells are more likely to exhibit Ca²⁺ oscillations at higher concentrations of [IP₃]_i (100-250 nm) than are COS-7 cells. Large increases in [IP₃]_i (>250 nm) induced the peak plateau-type Ca²⁺ response in both cell types.

FIGURE 6.

[Isqb]IP₃]_i in Ca²⁺-oscillating and Ca²⁺-nonoscillating cells. Cells were stimulated with various concentrations of ATP or carbachol, and [IP₃]_i in individual COS-7 (A) and HSY-EA1 cells (B) were plotted with distinction of Ca²⁺ oscillations (red circle), peak plateau-type response (open square), or no response (blue triangle). C and D show [IP₃]_i histograms for the % of oscillating COS-7 (C) and HSY-EA1 cells (D).

This study showed the time delay of IP₃ spike peaks from Ca²⁺ spike peaks in HSY-EA1 cells, and Ca²⁺ oscillations with nonfluctuations of [IP₃]_i in COS-7 cells. Together these results suggest it is likely that IP₃ spikes are not essential to drive Ca²⁺ oscillations. Regarding the mechanism of Ca²⁺ oscillations, the importance of dual feedback effects of Ca²⁺ on IP₃Rs has been demonstrated experimentally (6-8). However, it has been pointed out that this dual feedback effect explains relatively short period Ca²⁺ oscillations, but it cannot reproduce long interspike intervals. Thus, additional mechanisms responsible for establishing these oscillations remain unclear (3, 26, 27). One model study reported that frequency properties of oscillation are modulated by the incorporation of Ca²⁺ activation of PLC into the Ca²⁺ oscillation model based on dual feedback regulations of IP₃R properties, which enhances the range of frequency encodings of agonist stimulations (26). Interestingly, HSY-EA1 cells exhibited Ca²⁺ oscillations for a wider range of agonist and [IP₃]_i concentrations than observed in COS-7 cells. Thus, it may be possible that repetitive IP₃ spikes or fluctuations play some role in supporting and/or regulating Ca²⁺ oscillations. The quantitative information provided here would be useful for future studies of the mechanisms and roles of IP₃ oscillations.

Effect of [IP₃]_i on the Refractory Period of Ca²⁺ Oscillations—We analyzed the effects of [IP₃]_i on the interspike period of Ca²⁺ oscillations. In COS-7 cells, increases in agonist concentrations resulted in either shortening of interspike periods of Ca²⁺ oscillations (Fig. 5A) or shifting of oscillations to the peak plateau-type Ca²⁺ response (Fig. 5B) in association with increases in [IP₃]_i. Similarly, in HSY-EA1 cells, the interspike period of Ca²⁺ oscillations appeared to be correlated inversely with the increase in interspike levels of [IP₃]_i rather than the spike peak level (Fig. 5, C and D). These observations agree with observations that the refractory period of Ca²⁺ oscillations is controlled by [IP₃]_i (7, 8).

However, interspike periods of Ca²⁺ oscillations occurring during a slow rise in [IP₃]_i were not shortened by the rise in [IP₃]_i (Fig. 5, A and C). Small increases or no change in interspike periods during an increase in [IP₃]_i was observed in 18 of 55 HSY-EA1 cells and in 12 of 25 COS-7 cells. These data suggest that IP₃ is an important, but not exclusive, regulator of Ca²⁺ oscillation frequency.

Although the mechanism underlying the dissociation of the interspike period from the rise in [IP₃]_i is unknown, it might be associated with decreases in IP₃R sensitivity. Consistent with this idea, Matsu-ura et al. (11) described progressive decreases in apparent IP₃ sensitivity for generation of Ca²⁺ spikes during Ca²⁺ oscillations. It is known that Ca²⁺ within the lumen of the endoplasmic reticulum regulates IP₃R sensitivity. Thus, a slow rise in [IP₃]_i may be balanced by a decrease in IP₃R sensitivity via a slow decrease in stored Ca²⁺ (28). In addition, the involvement of stored Ca²⁺ and sarco/endoplasmic reticulum Ca²⁺-ATPase activity in determining the frequency of Ca²⁺ oscillations has been proposed recently (27). Additional work is required to explore the possible involvement of stored Ca²⁺ and other cytosolic factors in controlling the frequency of Ca²⁺ oscillations.

In summary, we developed improved IP₃ biosensors and a relatively simple method for the quantitative measurement of [IP₃]_i, and we applied this method for monitoring IP₃ dynamics during Ca²⁺ oscillations. This method revealed cell type-specific differences in IP₃ dynamics as follows: nonfluctuating rises in [IP₃]_i and repetitive IP₃ spikes. Our results provide the first quantitative information for repetitive IP₃ spikes and present new aspects concerning the regulation of Ca²⁺ oscillation frequency. In addition, the method demonstrated here offers a powerful means for studying the IP₃ dynamics of many cellular processes.