Cellular mechanisms underlying prostaglandin-induced transient cAMP signals near the plasma membrane of HEK-293 cells

Abstract

We have previously used cyclic nucleotide-gated (CNG) channels as sensors to measure cAMP signals in human embryonic kidney (HEK)-293 cells. We found that prostaglandin E₁ (PGE₁) triggered transient increases in cAMP concentration near the plasma membrane, whereas total cAMP levels rose to a steady plateau over the same time course. In addition, we presented evidence that the decline in the near-membrane cAMP levels was due primarily to a PGE₁-induced stimulation of phosphodiesterase (PDE) activity, and that the differences between near-membrane and total cAMP levels were largely due to diffusional barriers and differential PDE activity. Here, we examine the mechanisms regulating transient, near-membrane cAMP signals. We observed that 5-min stimulation of HEK-293 cells with prostaglandins triggered a two- to threefold increase in PDE4 activity. Extracellular application of H89 (a PKA inhibitor) inhibited stimulation of PDE4 activity. Similarly, when we used CNG channels to monitor cAMP signals we found that both extracellular and intracellular (via the whole-cell patch pipette) application of H89, or the highly selective PKA inhibitor, PKI, prevented the decline in prostaglandin-induced responses. Following pretreatment with rolipram (a PDE4 inhibitor), H89 had little or no effect on near-membrane or total cAMP levels. Furthermore, disrupting the subcellular localization of PKA with the A-kinase anchoring protein (AKAP) disruptor Ht31 prevented the decline in the transient response. Based on these data we developed a plausible kinetic model that describes prostaglandin-induced cAMP signals. This model has allowed us to quantitatively demonstrate the importance of PKA-mediated stimulation of PDE4 activity in shaping near-membrane cAMP signals.

Cyclic amp (cAMP) is an ubiquitous second messenger known to regulate diverse cellular functions (45). Although the basic mechanisms by which cAMP signals transmit information to downstream effectors have been well established, we are only beginning to unravel how these signals differentially regulate a wide variety of cellular responses over vastly different time-scales. One hypothesis is that cAMP signals are compartmentalized in different regions of the cell. In fact, this hypothesis emerged over 20 years ago to explain how different extracellular stimuli that primarily act through cAMP can have distinct downstream effects on the cell (4, 44). In recent years several groups have presented evidence implicating diffusional restrictions (31, 32), phosphodiesterase (PDE) activity (1, 23, 26, 32, 34, 49), and buffering by protein kinase A (PKA) (2, 7, 33, 39) as critical factors in shaping cAMP signals. Given the importance of these signals in cellular physiology, it is striking that little is known about the kinetics and subcellular localization of cAMP. One reason for the dearth of information is that until recently there have been no practical, single-cell cAMP sensors. In the past several years a series of genetically-encoded cAMP sensors based on cyclic nucleotide-gated (CNG) channels (31, 34), PKA (26), and EPAC (exchange proteins directly activated by cAMP) (8, 27, 29) have been developed. Direct binding of cAMP to each of these proteins triggers a conformational change that can be monitored by fluorescence resonance energy transfer (EPAC and PKA) or electrophysiological methods (CNG channels). The time course of these conformational changes has been best studied for CNG channels and PKA. The overall kinetics of CNG channels are much faster than PKA, and CNG channels have a much lower buffering capacity than heterologously expressed PKA. These factors make CNG channels better suited to measure fast cAMP responses near the plasma membrane (reviewed in Ref. 33). Less is known about the kinetics and buffering capacity of the EPAC-based sensors, but they do have potential advantages over PKA-based sensors (lower cAMP buffering capacity), and CNG channels (monitoring cytosolic cAMP signals) (see Refs. 8, 27).

When using these approaches one must be keenly aware of their advantages and disadvantages, and pick the sensor best suited to measure a specific signal. Two critical factors are the sensor’s kinetics and buffering capacity (33). We have previously taken advantage of the rapid kinetics and low buffering capacity of CNG channel-based sensors to examine the sub-cellular compartmentalization of cAMP signals. We observed that 1) cAMP concentrations near the plasma membrane were >10-fold higher than total cAMP levels in C6–2B glioma cells and human embryonic kidney (HEK)-293 cells stably overexpressing adenylyl cyclase (AC) type 8; 2) cAMP accumulation at the plasma membrane was resistant to dialysis in the whole-cell, patch-clamp configuration; and 3) the wash-in of cAMP from the patch pipette to the channels was anomalously slow (31). In addition, we developed a compartmental model of cAMP signaling that was able to describe all of these results. The model predicted that in response to a stimulus, kinetically distinct cAMP signals could be observed within cells, and that cyclic nucleotides produced from distinct pools of cyclase (e.g., particulate and soluble guanylyl cyclase) would not have the same efficacy in activating CNG channels, even if similar total cellular cyclic nucleotide levels were reached. We have subsequently provided evidence supporting both predictions (28, 32). As part of the former study we found that prostaglandin E₁ (PGE₁) triggers a transient cAMP signal near the plasma membrane of these cells, and presented evidence that the decline in the signal was primarily due to a PGE₁-induced stimulation of PDE activity.

Here, we have used CNG channel-based sensors to more closely examine the underlying mechanisms responsible for transient cAMP signals near the plasma membrane. Our results demonstrate that PKA-mediated stimulation of PDE4 activity underlies the decline in transient cAMP signals, and that the subcellular localization of PKA via A kinase anchoring proteins (AKAPs) is critical in the regulation of these signals. We used these data to develop a plausible kinetic model of near-membrane cAMP signals. The simulations demonstrate that stimulation of PDE4 activity is sufficient to cause the observed decline in transient cAMP signals. Furthermore, based on these simulations we propose that high local concentrations of PKA serve to buffer cAMP, contributing to its slow spatial spread within cells (23, 28, 31, 40). Resolving the kinetics of the near-membrane cAMP signals in this relatively simple cellular system should help us better understand the physiological consequences of PDE4 regulation and the mechanisms by which cAMP is localized to different cellular compartments.

MATERIALS AND METHODS

Cell culture and channel expression

HEK-293 cells were maintained in culture and transfected using adenovirus constructs as described previously (31). Briefly, HEK-293 cells were maintained in 10 ml of MEM (Life Technologies) with 10% (vol/vol) fetal bovine serum (Gemini), and grown in 100-mm culture dishes at 37°C in a humidified atmosphere of 95% air-5% CO₂. Cells were plated at ~60% confluence in 100-mm dishes for infection with the C460W/E583M CNG-channel-encoding adenovirus construct (multiplicity of infection ~10 plaque-forming units/cell) (34). Two hours postinfection, hydroxyurea was added to the cell media at 1 mM final concentration to inhibit viral replication. Twenty-four hours postinfection cells were detached with phosphate-buffered saline containing 0.03% EDTA, resuspended in serum-containing media, and assayed within 12 h. All experiments were conducted at room temperature, 20–22°C. Unless otherwise stated all reagents were purchased from Sigma.

Measurement of PDE activity

Cyclic AMP PDE activity was measured according to the method of Thompson and Appleman (46) as detailed previously (16). Briefly, after incubation for 1–5 min with or without PGE₂ (1 μM), forskolin (50 μM), or isoproteronol (10 μM), cells were harvested and homogenized in ice-cold hypotonic buffer (in mM), 20 Tris·HCl, pH 8.0, 50 NaF, 1 EDTA, 0.2 EGTA, 10 Na₂PO₄, 5 β-mercaptoethanol, and a protease inhibitor cocktail [leupeptin, 0.5 μg/ml; aprotinin, 4 μg/ml; benzamidine, 50 mM; pepstatin, 0.7 μg/ml; soybean trypsin inhibitor, 10 μg/ml; and PMSF, 10 μg/ml (freshly added before use)] using an all-glass homogenizer. In some experiments, homogenates were centrifuged at 14,000 g for 15 min and the supernatant (soluble) and pellets (particulate fraction) were assayed separately. Aliquots of the homogenates or of the fractionated extracts were assayed for PDE activities with 1 μM [³H]cAMP as a substrate. PDE4 activity was defined as the fraction of cAMP PDE activity inhibited by 10 μM rolipram (a PDE4 inhibitor). Protein concentrations were determined using the Bio-Rad protein assay (Bio-Rad Laboratories, Hercules, CA) with BSA as a standard. Experiments were repeated at least three times.

Western blot analysis

After incubation with the indicated substances, cells were homogenized in ice-cold hypotonic buffer and the protein concentration was determined. Samples (40 μg protein) were boiled in Laemmli buffer (25), subjected to electrophoresis on an 8% SDS-PAGE gel, and blotted onto Immobilon-P transfer membrane (Millipore, Bedford, MA). Membranes were blocked in TBS-0.1% Tween 20 containing 5% nonfat milk. The phosphorylated and total cAMP response element binding (CREB)/activating transcription factor (ATF) proteins were detected using mouse monoclonal (Upstate Biotechnology) and rabbit polyclonal antibodies (Cell Signaling), respectively and visualized by use of ECL detection reagents (Amersham Pharmacia Biotech).

Measurement of total cellular cAMP levels

HEK-293 cells were plated at 33% confluence in 12-well plates and assayed 24–48 h later. Cells were washed and assayed in a solution containing (in mM), 145 NaCl, 4 KCl, 10 HEPES, 10 D-glucose, 1 MgCl₂, 1 CaCl₂, pH 7.4. Additions were made from 100× stock solutions. Reactions were terminated by addition of 1 N HCl (0.1 N HCl final) and plates were incubated on ice for 15 min, after which the cells were scraped from the well. Cellular cAMP levels were measured using enzyme immunoassays (Direct Cyclic AMP Enzyme Immunoassay Kit, Assay Designs). Sample cAMP concentrations were calculated from standard curves. Data are presented as means ± SE, performed in triplicate.

Monitoring near-membrane cAMP signals in cell populations

Cyclic AMP signals were monitored in cell populations as described previously (32–34). Briefly, we took advantage of the Ca²⁺ permeability of CNG channels comprised of the rat olfactory channel α subunits, CNGA2 (14), and measured the rate of Ca²⁺ influx to monitor changes in cAMP levels. In this assay, an increase in local cAMP concentration causes activation of CNG channels and a subsequent increase in the rate of Ca²⁺ entry (12, 31–34). Changes in the rate of Ca²⁺ influx in response to stimuli reflect changes in the cAMP levels. We used the fluorescent indicator fura-2 to monitor Ca²⁺ influx in cell populations. Cells were loaded with 4 μM fura-2 AM (the membrane-permeant form, Calbiochem) at room temperature, 20–22°C, for 30–40 min, in MEM supplemented with 20 mM HEPES, pH 7.4. Cells were washed twice, then resuspended in a solution containing (in mM), 145 NaCl, 11 D-glucose, 10 HEPES, 4 KCl, 1 CaCl₂, and 1 MgCl₂, pH 7.4 (3–4 × 10⁶ cells/3 ml buffer solution), and assayed using a PTI DeltaScan-1 spectrofluorimeter (Photon Technology International). PGE₁, PGE₂, rolipram, and the PKA inhibitor H89 (Calbiochem) were added to a stirred cuvette from concentrated DMSO stocks, with final concentrations as indicated (final DMSO concentrations were ≤0.2%). The mixing time was estimated to be on the order of 5 s. Fluorescence was measured at an excitation wavelength of 380 nm and an emission wavelength of 510 nm. Under these conditions Ca²⁺ influx caused a decrease in fluorescence (ΔF), which was expressed relative to the prestimulus fluorescence (F₀) to correct for variations in dye concentration, and to allow for comparison of results on different batches of cells. Data were sampled at either 5 or 10 Hz and filtered at 0.5 or 1 Hz. All data are representative of at least four experiments.

To ensure that extracellular application of H89 did not alter the Ca²⁺ handling properties of HEK-293 cells, we examined the effects of a 10 min pretreatment with 10 μM H89 on thapsigargin-induced changes in intracellular Ca²⁺ levels. Pretreatment with H89 did not significantly change the Ca²⁺ response induced by 1 μM thapsigargin in nominally Ca²⁺-free conditions (Ca²⁺ release from internal stores), or in the presence of 1 mM extracellular Ca²⁺ (Ca²⁺ release from internal stores and subsequent Ca²⁺ entry). Thus, it is unlikely that H89 significantly altered the Ca²⁺ handling properties of the cells.

Monitoring near-membrane cAMP signals in single cells

Single-cell cAMP measurements were made using the whole-cell, patch-clamp technique. Recordings were made using an HEKA EPC10 patch-clamp amplifier. To ensure adequate voltage control, pipette resistance was limited to 4 MΩ and averaged 2.6 ± 0.2 MΩ (n = 43). Voltage offsets were zeroed with the pipette in the bath solution; no additional corrections were made for the liquid junction potential difference. Experiments with a series resistance-induced error in excess of 5 mV were discarded. After achieving whole-cell configuration, the preparation was allowed to equilibrate for at least 10 min to ensure sufficient time for dialysis of compounds from the patch pipette into the cell. Current records were typically sampled at 10 kHz and filtered at 2 kHz and stored on a PC. Currents were recorded during 400-ms steps to a membrane potential of +20 mV from a holding potential of 0 mV. The pipette solution contained (in mM) 140 KCl, 0.5 MgCl₂, 10 HEPES, 5 Na₂ATP, 0.5 Na₂GTP, pH 7.4; the bath solution contained (in mM) 140 NaCl, 4 KCl, 10 D-glucose, 10 HEPES, and either 0.1 or 10 MgCl₂, pH 7.4. PGE₁ and rolipram (Calbiochem) were added to control solutions from concentrated DMSO stocks (final DMSO concentrations ≤0.2%), with final concentrations as indicated. PKI (Calbiochem), stearated (St)-Ht31 (Pro-mega), H89, and St-Ht31P control peptide (Promega) were aliquoted as 1,000× stock solutions and stored at −20°C. Solutions were applied using the SF-77B fast-step solution switcher (Warner Instruments). The mechanical switch time was 1–2 ms. The time required to exchange the extracellular solution was measured by applying a 140 mM KCl solution to a depolarized cell (+50 mV) and monitoring changes in current through endogenous voltage-gated K⁺ channels; for each experiment, it was less than 100 ms. The bulk solution within the bath chamber was changed within 20 s using a custom-built, gravity-driven perfusion system.

Data analysis and mathematical simulations

All data were analyzed using custom scripts written in the MATLAB programming environment (MathWorks) and statistical analysis was performed using SigmaPlot (v.9; Systat Software) using Student’s t-test. Electrophysiological data were converted to formats compatible with MATLAB software using a custom script provided by Bruxton. Simulations were performed using the fourth-order Runge-Kutta solver in the MATLAB programming environment.

RESULTS

Recent studies have demonstrated that PDE4D5 and PDE4D9 are responsible for the majority of endogenous PDE activity in HEK-293 cells (36). Consistent with these results, we have demonstrated that PDE4 is primarily responsible for the IBMX-sensitive PDE activity near the plasma membrane of these cells (34). We have also provided evidence suggesting that stimulation of PDE4 activity was largely responsible for the decline in cAMP levels following PGE₁-stimulation of HEK-293 cells (32). Here we sought to determine the mechanisms that underlie feedback regulation of cAMP signals near the plasma membrane of these cells. One interesting possibility is that PKA-mediated phosphorylation of PDE4 increases PDE activity, causing the observed decline in the transient cAMP signals.

Effects of H89 on PDE4 and AC activity

To determine the extent to which prostaglandins induce activation of PDE4, we exposed HEK-293 cells to vehicle or 1 μM PGE₂ for different times and then measured PDE4 activity in either the crude homogenate, or in the soluble and particulate fractions. PDE4 activity was determined as the rolipram-sensitive PDE activity. PGE₂ treatment triggered a two- to threefold increase in PDE4 activity in both the soluble and particulate fractions of the cells (Fig. 1, A and B) as well as in the homogenate (data not shown). An increase in activity was detected as early as 1 min after PGE₂ addition (Fig. 1, A and B). The increase in PDE4 activity was recovered in the pellet after immunoprecipitation with PDE4D-selective antibodies (data not shown), suggesting that activation of this isoenzyme plays a major role in this G protein-coupled receptor (GPCR)-dependent regulation of cAMP signals. Pretreatment of cells for 10 min with the PKA inhibitor H89 reduced the PGE₂-induced stimulation of PDE4 activity in a dose-dependent manner (Fig. 1C). Half-maximal inhibition of PGE₂-stimulated PDE activity occurred following pretreatment with ~4 μM H89, and complete inhibition occurred at 10 μM H89. Similar results were observed following 10 μM isoproterenol-induced or 100 μM forskolin (an AC activator)-induced stimulation of cAMP production (data not shown).

Fig. 1.

PKA-dependent regulation of phosphodiesterase (PDE)4 by PGE₂ in human embryonic kidney (HEK)-293 cells. A and B: time course of PDE4 activation in the soluble (A) and particulate (B) fractions of HEK-293 cell extracts. Cells were incubated for the times indicated in the abscissa with 1 μM PGE₂. At the end of the incubation, cells were harvested and homogenates fractionated by centrifugation as detailed in Materials and Methods. Aliquots of the supernatant or the resuspended pellet were used to measure PDE activity using 1 μM cAMP as substrate in the absence or presence of 10 μM rolipram (a PDE4 inhibitor). The rolipram-inhibited PDE activity (PDE4 activity) is reported. Data are the means ± SE of three separate experiments each carried out in triplicate. C: H89 (a PKA inhibitor) inhibition of the PGE₂-stimulated PDE4 activity in HEK-293 cells. Cells were preincubated in the absence or presence of the increasing concentrations of H89 reported in the abscissa. After 10 min, cells were stimulated with 1 μM PGE₂ for an additional 5 min. At the end of the incubation, the PDE activity in the homogenate was measured as detailed in MATERIALS AND METHODS. PGE₂ at 1 μM significantly increased PDE4 activity (P ≤ 0.05). The stimulation of PDE4 activity was inhibited by pretreatment with 10 μM H89 (P ≤ 0.05). Significance was evaluated using Student’s t-test. D: cells were stimulated with PGE₂ as described in (C). Incubation was terminated by the addition of sample buffer, and protein in the cell extract was fractionated by SDS-PAGE and transferred to nylon membranes. After blocking, blots were probed with phospho-specific cAMP response element binding protein (CREB) antibodies. After the first exposure, blots were stripped and reprobed with a CREB antibody. Data are reported as the ratio between the phospho-CREB and the CREB signals quantified by image analysis. A representative experiment of the three performed is reported.

The extracellular concentrations of H89 used in these experiments were significantly higher than the reported K_I for PKA, ~40 nM (17), and could potentially inhibit other protein kinases. However, under these conditions we were unable to estimate the intracellular H89 concentrations. To ensure that H89 was indeed inhibiting PKA, we tested the dose dependence of H89 inhibition of CREB phosphorylation in the same preparation. Under these experimental conditions, H89 inhibited CREB phosphorylation with a similar dose dependence as it inhibited PDE4 stimulation (Fig. 1D). In control experiments, pretreatment with 1–30 μM H85, an analog of H89 that does not inhibit PKA, had little or no effect on prostaglandin-induced stimulation of PDE4 activity or CREB phosphorylation (data not shown).

We next examined the effects of H89 and rolipram on forskolin-, PGE₁-, and PGE₂-induced total cellular cAMP accumulation using enzyme immunoassays (Fig. 2). In response to vehicle alone (5 min) 0.9 ± 0.3 pmol/well of cAMP was measured, and there was no significant increase in cAMP levels following 10 min pretreatment with 10 μM H89 alone (open bars), pretreatment with 10 μM rolipram alone (cross-hatched bars) or H89 and rolipram (hatched bars). Stimulation with a subsaturating concentration of forskolin (1 μM, 5 min) triggered no significant increases in total intracellular cAMP, whereas PGE₁ and PGE₂ (1 μM, 5 min) triggered significant increases (~3-fold over vehicle alone). Pretreatment with H89, rolipram, or H89 + rolipram triggered significant increases in forskolin- and prostaglandin-induced cAMP accumulation. There were no significant differences between the prostaglandin-induced cAMP accumulation observed following pre-treatment with rolipram alone vs. H89 + rolipram, indicating that the primary effect of H89 was the inhibition of prostaglandin-induced stimulation of PDE4 activity. This is consistent with our previous work that demonstrated the rate of total cAMP accumulation is nearly linear in the presence of PDE inhibitors (see figure 1B of Ref. 32).

Fig. 2.

PKA activity does not significantly inhibit endogenous prostanoid receptor or adenylyl cyclase (AC) activity in HEK-293 cells. Cyclic AMP accumulation was measured with enzyme immunoassays. HEK-293 cells (0.9 × 10⁶/well) were stimulated for 5 min with 1 μM forskolin, 1 μM PGE₁, or 1 μM PGE₂ (as indicated) following pretreatment with vehicle (solid bars), 10 μM H89 (10 min, open bars), 10 μM rolipram (5 min, cross-hatched bars), or 10 μM H89 + 10 μM rolipram (hatched bars). H89 had little or no effect on prostaglandin-induced cAMP accumulation (5 min) in the presence of rolipram. Pretreatment with H89, rolipram, or H89 + rolipram causes significant increases in agonist-induced cAMP accumulation. Significance was evaluated using Student’s t-test, *P < 0.05. Similar results were obtained with 10 μM H89 and 100 μM IBMX (data not shown). These data indicate that H89 has little effect on the endogenous AC activity in HEK-293 cells. Data represent the means ± SE of three experiments conducted in triplicate.

Effects of H89 on cAMP signals monitored in cell populations

We next sought to determine the effects of H89 on the prostaglandin-induced cAMP transients that occur near the plasma membrane of HEK-293 cells. We used a previously developed CNGA2 ion channel construct, containing the mutations C460W and E583M (C460W/E583M channels), to measure near-membrane cAMP signals. These mutations make it possible to measure cAMP concentrations in the 100 nM range, while rendering the channel relatively insensitive to cGMP (32, 34). C460W/E583M channels were heterologously expressed using a previously described adenovirus construct (34). To determine the effects of extracellular application of H89 on near-membrane cAMP signals we monitored changes in CNG channel activity by measuring Ca²⁺-influx through the channels; the fluorescent indicator fura-2 was used to monitor changes in intracellular Ca²⁺ levels in cell populations. With this approach, incremental changes in cAMP concentration are readily detected as changes in relative Ca²⁺ influx rates through C460W/E583M channels. By observing CNG channel responses in cell populations we avoid the possibility of inadvertently biasing our data by selecting single cells that are best suited for electrophysiological measurements. As such, we consider these important control experiments that allow us to ensure data from single cells are consistent with data from cell populations.

Figure 3A shows a typical response to 0.1 and 1 μM PGE₁ in populations of HEK-293 cells (3–4 × 10⁶ cells per cuvette) expressing C460W/E583M channels. Addition of PGE₁ (added at 1 min, arrow) triggered an initial influx of Ca²⁺ through C460W/E583M channels, followed by a slower reduction in Ca²⁺ levels. Little or no response was observed in cells not expressing C460W/E583M channels. Pretreatment with 10 μM rolipram (3 min), a selective PDE4 inhibitor, prevented the decline in the responses triggered by either 0.1 or 1 μM PGE₁ (Fig. 3B). Ten minute pretreatment with 10 μM H89 dramatically reduced the decline in the PGE₁-induced responses (Fig. 3C). We determined that slopes of the PGE₁-induced responses following 10 min pretreatment with 10 μM H89 and 3 min pretreatment with 10 μM rolipram were not significantly different than slopes of the PGE₁-induced responses following pretreatment with rolipram alone (Fig. 3D). In control experiments, pretreatment with 10 μM H85 had little or no effect on prostaglandin-induced cAMP transients (data not shown). Also, pretreatment with 10 μM H89 had little or no effect on the time course or amplitude of Ca²⁺ influx in response to extracellular application of 100 μM pCPT-cGMP (a membrane permeant cGMP analog, data not shown), indicating that pre-treatment with 10 μM H89 had little or no effect on CNG channel activity. These data are consistent with the hypothesis that PKA-mediated stimulation of PDE4 activity is primarily responsible for the decay in the cAMP response.

Fig. 3.

Rolipram and H89 (PDE4 and PKA inhibitors) inhibit the decline in prostaglandin-induced transient cAMP signals. Near-membrane cAMP levels were monitored by measuring Ca²⁺ influx through C460W/E583M cyclic nucleotidegated (CNG) channels in response to 0.1 or 1 μM PGE₁ applied at 60 s (arrows). Addition of PGE₁ triggered a transient increase in intracellular Ca²⁺ (A). Three-minute pretreatment with 10 μM rolipram prevented the decline in the transient response induced by PGE₁ (B). Similarly, 10-min pre-treatment with 10 μM H89 inhibited the decline in the transient response (C). Pretreatment with both 10 μM H89 (10 min) and 10 μM rolipram (3 min) prevented the decline in the transient response (D). Similar results were obtained using PGE₂ (data not shown). Data are representative of at least 4 experiments.

Effects of disrupting PKA-mediated signaling on cAMP signals measured in single cells

Thus far we have focused our studies on using H89 to inhibit PKA-mediated effects in cell populations. By examining the dose-dependence of H89-mediated inhibition of CREB phosphorylation, we were able to choose an appropriate H89 concentration to inhibit PKA activity. In addition, we used H85 to control for potential non-kinase-specific effects of H89. However, it is possible that a 10 min pretreatment with 10 μM H89 may inhibit other kinases. To directly address this limitation we examined the effects of H89, PKI, a specific PKA inhibitor, and rolipram on cAMP signals measured in single cells using the whole-cell, patch-clamp technique. This high-resolution approach allows us to accurately measure the kinetics of prostaglandin-induced cAMP signals in single cells. In addition, compounds such as H89 or PKI can be introduced into the cell at known concentrations via the whole-cell patch pipette. Thus, we can accurately examine the dose-dependence of H89 or PKI effects on prostaglandin-induced cAMP signals. All electrophysiological experiments were conducted with nominally Ca²⁺-free buffers. Under these conditions the primary charge carriers through CNG channels are Na⁺ and K⁺. Thus, Ca²⁺ influx through CNG channels (and subsequent Ca²⁺-CaM mediated inhibition of CNG channel activity) did not contribute to the observed responses. No PGE₁-induced responses were observed in control cells (cells not expressing CNG channels) or in cells expressing wild-type CNGA2 subunits (K_1/2 for cAMP ~40 μM).

Figure 4A shows a typical response of an HEK-293 cell expressing C460W/E583M channels to 1 μM PGE₁. In this cell, PGE₁ triggered a transient increase in outward current through C460W/E583M channels. This response is consistent with the PGE₁-induced responses that we previously reported (32). Pretreatment of cells with 10 μM rolipram largely prevented the decline in the response (Fig. 4, B and D). Addition of rolipram following a PGE₁-induced transient response triggered a large increase in current through CNG channels (Fig. 4C). These data demonstrate that the exposure of cells to PGE₁ does not trigger cAMP accumulation to levels that saturate CNG channels, and are consistent with calibrated measurements of cAMP concentration near CNG channels, 0.7 ± 0.4 μM (32). To assess the extent to which rolipram prevented the decline in the cAMP response, we measured the percentage current remaining 3 min after peak current. In cells in which vehicle (0.1% DMSO) was added to the patch pipette solution 26 ± 6% of the peak current remained, whereas in cells that were pretreated with 10 μM rolipram, 92 ± 6% of the peak current remained (Fig. 4D).

Fig. 4.

Single-cell measurement of PGE₁-induced cAMP signals. A: outward currents through CNG channels revealed a transient increase in cAMP level in response to bath application of 1 μM PGE₁. Currents were measured in the whole-cell, patch-clamp configuration during 400-ms steps to a test potential of +20 mV, from a holding potential of 0 mV. Dotted lines indicate zero current. B: single cell response in which the cell was pretreated for 5 min with 10 μM rolipram before exposure to 1 μM PGE₁. C: single cell response in which the cell was initially exposed to 1 μM PGE₁ prior to exposure to 10 μM rolipram + 1 μM PGE₁ (at indicated times). These data clearly indicate that PGE₁-induced cAMP accumulation did not saturate the CNG channels. D: data similar to those shown in A and B were quantified by measuring the percentage of current remaining 3 min after the peak current. Following pretreatment with rolipram, the decline in the PGE₁-induced current was significantly reduced. Data are given as means ± SE. Significance was evaluated using Student’s t-test (***P ≤ 0.01). No PGE₁-induced currents were observed in cells not expressing CNG channels (n = 7).

We examined the effects of known intracellular H89 concentrations on the cAMP signals monitored in single cells (Fig. 5). In the presence of 100 nM H89 (~2.5-fold higher than the K_I for PKA, and significantly lower than the K_I for other kinases), the rise in PGE₁-induced responses was similar to that observed in control cells, whereas the decay was markedly less pronounced (compare Fig. 5A with Fig. 4A). At 200 nM H89 the decay was even less pronounced (Fig. 5B). Addition of H89 to the patch pipette increased the percentage of current remaining in a dose-dependent manner (a maximum of ~68% in the presence of 0.5 or 1 μM H89, Fig. 5C). To further demonstrate the role of PKA-mediated feedback control of cAMP signals we used the highly specific PKA inhibitor PKI, K_I ~ 2.3 nM (6). We introduced PKI into the cell via the patch pipette because it does not readily cross the plasma membrane. In the presence of either 5 or 20 nM PKI, the decay of the responses was dramatically blunted (Fig. 6, A and B), with 81 ± 6% and 85 ± 4% current, respectively, remaining 3 min after the peak response (Fig. 6C). Taken together, the results presented thus far strongly indicate that PKA-mediated stimulation of PDE4 activity is required for the decline in the PGE₁-triggered transient cAMP response.

Fig. 5.

Low intracellular concentrations of H89 inhibit the decay of cAMP signals measured in single HEK-293 cells. A and B: the response of cells to 1 μM PGE₁ with 100 or 200 nM H89 included in the whole-cell, patch pipette solution. The pipette solution was allowed to equilibrate with the cell for at least 10 min after achieving whole-cell configuration. The decay of the transient response was significantly reduced in an H89 dose-dependent manner. Application of 10 mM MgCl₂ blocked the PGE₁-induced currents. The dotted lines indicate zero current. C: to quantify the results we measured the percentage of current remaining 3 min after the peak current. The H89 dose-dependence is consistent with H89 inhibition of PKA activity, and thus supports the hypothesis that PKA-mediated phosphorylation of PDE4 stimulates PDE activity, which is the primary factor in the decay of the transient PGE₁-induced cAMP signal. The number of experiments is indicated in parentheses. Data are given as means ± SE. Significance was evaluated using Student’s t-test (*P ≤ 0.05, **P ≤ 0.02, ***P ≤ 0.01).

Fig. 6.

PKI, a highly selective PKA inhibitor, inhibits the decay of cAMP signals measured in single HEK-293 cells. A and B: 1 μM PGE₁ triggered outward current through CNG channels in whole-cell configuration (monitored during steps to +20 mV). Both 5 nM (A) and 20 nM (B) PKI significantly inhibited the decay of the transient cAMP response. Currents were subsequently blocked by 10 mM MgCl₂. Dotted lines indicate zero current. C: to quantify the results we measured the percentage of current remaining 3 min after the peak current. Inhibition of the decay in the transient response by 5 and 20 nM PKI provide strong evidence that PKA-mediated phosphorylation of PDE4 is responsible for the observed increase in PDE activity. Data are given as means ± SE. The number of experiments is indicated in parentheses. Significance was evaluated using Student’s t-test (***P < 0.01).

We next sought to determine whether disruption of AKAPs would also alter the kinetics of PGE₁-stimulated cAMP signals. We monitored PGE₁-induced responses with an AKAP inhibitor peptide, Ht31, or the associated control peptide, Ht31P, in the patch pipette (Fig. 7). Ht31 is a peptide with an amphipathic helix motif that is a competitive inhibitor of all known PKA-AKAP interactions. Ht31P is a related peptide that has a proline in the sequence, which disrupts the amphipathic helix and binding to AKAPs (5). We found that including 10 μM Ht31 in the patch pipette solution caused a delay in and reduction of the rate of decay of PGE₁-induced cAMP signals (Fig. 7A). In fact, 93 ± 3% of the current remained 3 min after the peak response (Fig. 7C). Transient PGE₁-induced responses were still evident when 10 μM control peptide was included in the patch pipette (Fig. 7, B and C). These data clearly show the profound effects that the disruption of AKAPs has on cAMP signals.

Fig. 7.

The AKAP inhibitor peptide Ht31 inhibits the decline in PGE₁-induced cAMP signals. A and B: 10 μM stearated (St)-Ht31, but not the control peptide, significantly inhibited the decay in PGE₁-induced transient cAMP responses monitored using the whole-cell, patch-clamp configuration. C: to quantify the results we measured the percentage of current remaining 3 min after the peak current. Inhibition of the decay in the transient response by 10 μM Ht31 provides strong evidence that AKAP-mediated subcellular localization of PKA is critical for PKA-mediated stimulation of PDE4 activity. Data are given as means ± SE. The number of experiments is indicated in parentheses. Significance was evaluated using Student’s t-test (***P ≤ 0.01).

Roles of PKA-mediated stimulation of PDE4 and cAMP buffering in shaping cAMP signals

To further investigate the relative contributions of PDE activity and buffering in shaping cAMP signals we developed a plausible kinetic model of cAMP turnover near the plasma membrane of HEK-293 cells. Figure 8 depicts the primary feedback mechanism controlling PDE4 activity in response to prostaglandin-induced cAMP signals (at least in the first 5 min of stimulation). In this model PKA influences the time course of cAMP signals by stimulating PDE4 activity and by buffering cAMP (reducing free cAMP levels). AKAPs are required to concentrate PKA activity near PDEs. The equations used to describe this model are given below. Parameters and initial conditions are given in Table 1.

Fig. 8.

Schematic of the feedback mechanism that increases PDE4 activity. Ligand binding to the prostaglandin (EP) receptor leads to activation of stimulatory G protein (G_s), activation of AC, and stimulation of cAMP synthesis. Binding of cAMP to the regulatory subunit of PKA releases the catalytic subunit and buffers free cAMP levels. PKA-mediated phosphorylation of PDE4 triggers a 2- to 3-fold increase in the V_max. The increase in PDE4 activity is primarily responsible for the reduction in free cAMP levels.

Table 1.

Parameters used to simulate transient cAMP signals near the plasma membrane of HEK-293 cells

Parameter	Value	Initial Condition	Reference
EAC0	0.12 μM·s−1		31, 32
τ	2,000 s		32
[N]		0.5 μM	2
[PDE]		0.8 μM	30, 32
kPDE	0.11 s−1		30, 32
[PDEp]		0.2 μM	*
kPDEp	3·kPDE		32
Km	0.7 μM		21
KI	0.1 μM		21, 35
K1/2	1.1 μM		32, 34
nH	2.1		32, 34
kPKA	0.0075 μM−1·s−1		†
kpp	0.0015 s−1		†
[PKA]	1 μM		2, 18, 33
kfa	5 μM−1·s−1		11, 33
kfb	0.4 μM−1·s−1		11, 33
kra	1 s−1		11, 19, 33
krb	0.2 s−1		11, 19, 33
kact	70 s−1		19, 22, 33, 43
kdeact	0.75 μM−2·s−1		19, 22, 33, 43
KI-PKI	2.3 nM		6

^*Denotes value derived from reference above. Initial conditions were estimated based on steady-state parameter values in the absence of cAMP synthesis or degradation.

^†Denotes values were fit to the time course of cAMP decay. The sensitivity of the model to parameters is demonstrated by examining the effects of altering phosphodiesterase (PDE) activity, PKA concentration, and τ (Fig. 10).

$$\frac{\mathrm{d}[\mathrm{N}]}{\mathrm{d}t}=E_{\mathrm{A}C}-\frac{[\text{PDE}]·[\text{cAMP}]·k_{\text{PDE}}}{[\text{cAMP}]+K_{\mathrm{m}}·\left(1+\frac{[\mathrm{I}]}{K_{\mathrm{I}}}\right)}-\frac{[\text{PDEp}]·[\text{cAMP}]·k_{\text{PDEp}}}{[\text{cAMP}]+K_{\mathrm{m}}·\left(1+\frac{[\mathrm{I}]}{K_{\mathrm{I}}}\right)}$$ (1)

where, [N] is the total cAMP concentration, [cAMP] is the concentration of free cAMP, E_AC is the cAMP synthesis rate, [PDE] is the concentration of unphosphorylated PDE4, k_PDE is the cAMP hydrolysis rate constant for unphosphorylated PDE4, [PDEp] is the concentration of phosphorylated PDE4, k_PDEp is the cAMP hydrolysis rate constant for phosphorylated PDE4, K_m is the Michaelis constant for PDE4, [I] is the concentration of a competitive inhibitor such as rolipram, and K_I is the inhibition constant. The phosphorylation of PDE4 is described by the equations below.

$$\frac{\mathrm{d}[\text{PDE}]}{\mathrm{d}t}=-\frac{k_{\mathit{PKA}}}{1+\frac{[\text{PKI}]}{K_{\mathrm{I}-\text{PKI}}}}·[\mathrm{C}]·[\text{PDE}]+k_{\text{pp}}·[\text{PDEp}]$$ (2)

$$\frac{\mathrm{d}[\text{PDEp}]}{\mathrm{d}t}=\frac{k_{\text{PKA}}}{1+\frac{[\text{PKI}]}{K_{\mathrm{I}-\text{PKI}}}}·[\mathrm{C}]·[\text{PDE}]-k_{\text{pp}}·[\text{PDEp}]$$ (3)

where, k_PKA is the rate constant of PKA-mediated phosphorylation, K_I-PKI is the inhibition constant for the noncompetitive inhibitor PKI, k_pp is the rate constant of phosphatase-mediated dephosphorylation, and [C] is the concentration of free catalytic PKA subunits. The time-dependent reduction in the rate of cAMP synthesis is approximated by

$$E_{\text{AC}}=E_{\text{AC}0}·e^{-t/\mathrm{\tau }}$$ (4)

where, E_AC0 is the initial rate of cAMP synthesis and τ is the time constant for the reduction in the synthesis rate. This reduction in cAMP synthesis may be due feedback regulation of AC activity or a small amount of receptor desensitization. The equations describing PKA activity are given below.

$$\frac{\mathrm{d}[\mathrm{R}]}{\mathrm{d}t}=-(k_{\text{fa}}+k_{\text{fb}})·[\text{cAMP}]·[\mathrm{R}]+k_{\text{ra}}·[{\mathrm{R}}_{\mathrm{a}}]+k_{\text{rb}}·[{\mathrm{R}}_{\mathrm{b}}]-k_{\text{deact}}·[\mathrm{R}]·[\mathrm{C}]·[\mathrm{C}]$$ (5)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\mathrm{a}}]}{\mathrm{d}t}=-k_{\text{fb}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{a}}]-k_{\text{ra}}·[{\mathrm{R}}_{\mathrm{a}}]+{\mathrm{k}}_{\text{fa}}·[\text{cAMP}]·[\mathrm{R}]+k_{\text{rb}}·[{\mathrm{R}}_{\text{ab}}]-k_{\text{deact}}·[{\mathrm{R}}_{\mathrm{a}}]·[\mathrm{C}]·[\mathrm{C}]$$ (6)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\mathrm{b}}]}{\mathrm{d}t}=-k_{\text{fa}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{b}}]-k_{\text{rb}}·[{\mathrm{R}}_{\mathrm{b}}]+k_{\text{fb}}·[\text{cAMP}]·[\mathrm{R}]+k_{\text{ra}}·[{\mathrm{R}}_{\text{ab}}]-k_{\text{deact}}·[{\mathrm{R}}_{\mathrm{b}}]·[\mathrm{C}]·[\mathrm{C}]$$ (7)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\text{ab}}]}{\mathrm{d}t}=-(k_{\text{rb}}+k_{\text{ra}})·[{\mathrm{R}}_{\text{ab}}]+k_{\text{fb}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{a}}]+k_{\text{fa}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{b}}]+k_{\text{act}}·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]$$ (8)

$$\frac{\mathrm{d}[\text{RC}]}{\mathrm{d}t}=-(k_{\text{fa}}+k_{\text{fb}})·[\text{cAMP}]·[\text{RC}]+k_{\text{ra}}·[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]+k_{\text{rb}}·[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]+k_{\text{deact}}·[\mathrm{R}]·[\mathrm{C}]·[\mathrm{C}]$$ (9)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]}{\mathrm{d}t}=-k_{\text{fb}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]-k_{\text{ra}}·[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]+k_{\text{fa}}·[\text{cAMP}]·[\text{RC}]+k_{\text{rb}}·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]+k_{\text{deact}}·[{\mathrm{R}}_{\mathrm{a}}]·[\mathrm{C}]·[\mathrm{C}]$$ (10)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]}{\mathrm{d}t}=-k_{\text{fa}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]-k_{\text{rb}}·[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]+k_{\text{fb}}·[\text{cAMP}]·[\text{RC}]+k_{\text{ra}}·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]+k_{\text{deact}}·[{\mathrm{R}}_{\mathrm{b}}]·[\mathrm{C}]·[\mathrm{C}]$$ (11)

$$\frac{\mathrm{d}[{\mathrm{R}}_{\text{ab}}\mathrm{C}]}{\mathrm{d}t}=-(k_{\text{rb}}+k_{\text{ra}}+k_{\text{act}})·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]+k_{\text{fb}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]+k_{\text{fa}}·[\text{cAMP}]·[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]$$ (12)

$$\frac{\mathrm{d}[\mathrm{C}]}{dt}=-k_{\text{deact}}·[\mathrm{C}]·[\mathrm{C}]·([\mathrm{R}]+[{\mathrm{R}}_{\mathrm{a}}]+[{\mathrm{R}}_{\mathrm{b}}])+k_{\text{act}}·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]$$ (13)

where, R represents the regulatory subunit of PKA with two cAMP binding sites, a and b. [RC] is the concentration of unliganded regulatory subunits bound to catalytic subunits, [R_aC] is the concentration with cAMP bound to site a, [R_bC] is the concentration with cAMP bound to site b, [R_abC] is the concentration with cAMP bound to sites a and b. The rate constants for cAMP binding and unbinding to sites a and b are k_fa, k_fb, and k_ra, k_rb. The rate constants for the dissociation and association of the R and C subunits are k_act and k_deact. Note that the dissociation and association of the R and C subunits are considered irreversible reactions. The concentration of free cAMP and activation of CNG channels are described as follows

$$[\text{cAMP}]=[\mathrm{N}]-[{\mathrm{R}}_{\mathrm{a}}\mathrm{C}]-[{\mathrm{R}}_{\mathrm{b}}\mathrm{C}]-2·[{\mathrm{R}}_{\text{ab}}\mathrm{C}]-[{\mathrm{R}}_{\mathrm{a}}]-[{\mathrm{R}}_{\mathrm{b}}]-2·[{\mathrm{R}}_{\text{ab}}]$$ (14)

$$\frac{I}{I_{max}}=\frac{{[\text{cAMP}]}^{n_{\mathrm{H}}}}{{[\text{cAMP}]}^{n_{\mathrm{H}}}+{K_{1/2}}^{n_{\mathrm{H}}}}$$ (15)

where I/I_max is the fractional current through CNG channels, K_1/2 is the concentration of cAMP that elicits half-maximal current, and n_H is the Hill coefficient.

Simulations of the model are shown in Fig. 9. All simulations were initiated by a step increase in AC activity, analogous to the rapid application of prostaglandins. Under control conditions the increase in AC activity initiates a transient increase in cAMP and CNG channel activity. The amplitude of the CNG channel response (Fig. 9A) and underlying free cAMP signal (Fig. 9B) are consistent with calibrated responses previously measured using the perforated patch technique (32). The decline in the cAMP signal is primarily due to PKA-mediated stimulation of PDE4 activity. The simulation predicts that the total cAMP concentration (free and bound) near the plasma membrane is ~3-fold higher than the free cAMP concentration. This occurs because the free cAMP levels are significantly higher than the K_1/2 of PKA (200 nM), even after 300 s. Note that the total cAMP concentration near the plasma membrane would be higher if the PKA concentration were increased (due to the higher buffering capacity discussed below). We next used the model to examine the effects of PDE and PKA inhibitors (Fig. 9, D–F and G–I, respectively). In the presence of 10 μM rolipram, a competitive PDE4 inhibitor, cAMP levels quickly increase, saturating CNG channels (Fig. 9D). The model predicts that total cAMP levels near the plasma membrane reach 20 μM in 5 min, ~8-fold higher than control conditions. This is higher than the threefold increase in total cellular cAMP measured using enzyme immunoassays (Fig. 2). Factors that may contribute to these differences, and were not incorporated into the simulations, include mechanisms that segregate near-membrane and cytosolic cAMP signals (see Refs. 31, 32 for details), and incomplete equilibration of rolipram across the plasma membrane. Simulations using (intracellular) rolipram concentrations of 1–2 μM are consistent with the experimental observations presented in Fig. 2. In the presence of 20 nM PKI, a noncompetitive PKA inhibitor, cAMP levels reach a steady plateau in 5 min. This response demonstrates the importance of PKA-mediated stimulation of PDE4 activity in shaping the cAMP signal. Although basal levels of PDE4 activity are sufficient to prevent saturation of CNG channels (Fig. 9G) and to offset the rate of cAMP synthesis, they are not sufficient to cause the observed decline in cAMP levels.

Fig. 9.

Simulations of cAMP signals near the plasma membrane of HEK-293 cells. Equations for the simulations are described in the text, and parameters are given in Table 1. A–C depict CNG channel current (A), free cAMP concentrations (B), and the total cAMP levels (C) elicited in response to a step activation of AC (similar to what would be expected from rapid exposure to saturating concentrations of PGE₁ or PGE₂). The total cAMP levels represent free and bound cAMP near the plasma membrane (not total cellular cAMP levels). The overall time course and current remaining 3 min after the peak are similar to the experimental data presented in Figs. 3 and 4. D–F depict CNG channel current and cAMP levels elicited in the presence of 10 μM rolipram, a competitive PDE4 inhibitor. Free cAMP levels quickly rise to levels that saturate CNG channels (D and E), consistent with the data presented in Fig. 3. G–I depict the response in the presence of 20 nM PKI, a noncompetitive PKA inhibitor (K_I-PKI = 2.3 nM). Note that the basal PDE4 activity is sufficient to prevent cAMP from reaching levels that would saturate CNG channels.

We next sought to better understand the effects of PDE4 and PKA activity, as well as desensitization of cAMP synthesis rate (i.e., receptor desensitization or feedback inhibition of AC activity) on transient cAMP signals. We first examined the effects of altering k_PDE from the control value of 0.11 s⁻¹ (Fig. 10, A and B). A twofold reduction or increase in PDE4 activity dramatically altered the activation of CNG channels and the underlying free cAMP signals, either delaying the decline in free cAMP levels or dramatically reducing the amplitude of the response. These simulations clearly demonstrate the biological importance of maintaining precise control of PDE4 activity and the distribution of PDE4 within the cell. Altering the concentration of PKA also affected the time course of CNG channel activation and underlying cAMP signals (Fig. 10, C and D). Two- and fivefold increases in PKA concentration reduced the amplitude of the free cAMP signals, due to increased buffering and an increased phosphorylation rate, and created a significant lag in the activation of CNG channels. This simulation indicates that in cells with high local PKA concentrations, observed in a variety of cell types (13, 15, 26, 48), exposure to brief or subsaturating stimuli may activate PKA without activating lower affinity effectors such as endogenous CNG channels. Finally, a 10-fold reduction in τ had relatively small effects on the transient cAMP signals, primarily lowering peak and final cAMP levels (Fig. 10, E and F). This should not be surprising given that PKA-mediated stimulation of PDE4 activity has such profound effects on cAMP signals in this system. It is likely that processes such as receptor desensitization will have a greater impact on the time course of cAMP signals in systems in which stimulation of PDE activity does not dominate the response.

Fig. 10.

Effects of altering model parameters on CNG channel activity and underlying cAMP signals. In all panels the solid traces represent simulations with the parameters listed in Table 1. A and B depict the response to altered PDE4 activity (k_PDE). k_PDE values were 0.055 s⁻¹ (broken line), 0.11 s⁻¹ (solid line), 0.22 s⁻¹ (dashed line), and 0.44 s⁻¹ (dotted line), and k_PDEp values remained 3 · k_PDE. C and D depict the responses with PKA concentrations of 1 μM (solid line), 2 μM (broken line), 5 μM (dashed line) and 10 μM (dotted line). Note the significant lag in the activation of CNG channels in the presence of higher PKA concentrations. E and F depict the effects of decreasing τ, or increasing the rate at which cAMP production is reduced. In these simulations τ = 2,000 s (solid line), 1,000 s (broken line), 500 s (dashed line), or 200 s (dotted line).

DISCUSSION

Previous studies have demonstrated that PKA phosphorylates PDE4D, and that phosphorylation triggers an increase in PDE4D activity (3, 41, 42). In separate studies, investigators have examined the functional role of PDE4 activity in shaping cAMP signals (1, 24, 32, 34, 49). Here we combine elements of each approach to more closely examine the contributions of hydrolysis and buffering in regulating free cAMP levels near the plasma membrane of HEK-293 cells. We accomplished this by examining the cellular mechanisms responsible for the decline in transient, prostaglandin-induced cAMP signals. We found that inhibition of PKA activity with H89 prevented the stimulation of PDE4 activity, as well as the decline of the transient cAMP signals in cell populations. To more definitively implicate PKA-mediated regulation of PDE4 activity, we examined the effects of application of H89 and PKI at known intracellular concentrations. These compounds prevented the decline in transient cAMP responses within expected concentration ranges for inhibition of PKA activity. We also examined the effects of an AKAP disruptor, Ht31, on PGE₁-induced cAMP signals, and found that disruption of AKAPs significantly diminished the decline in transient cAMP responses. These results are consistent with recent studies that have shown HEK-293 cells express AKAPs 79 and 250 (20), and that AKAP 250 (gravin) plays a critical role in the subcellular localization of PKA and PDE4, as well as the kinetics of prostaglandin-induced cAMP signals (47). The effect of AKAP disruptors on these signals is likely to have occurred for two reasons: the reduction in catalytic subunit concentration lowered the rate at which PKA could phosphorylate PDE4, and the reduction in the regulatory subunit concentration lowered the local cAMP buffering capacity.

A study by DiPilato et al. (8) used fluorescent cAMP indicators based on EPAC to examine the dynamics of cAMP signals in HEK-293 cells. The EPAC-based sensors were targeted to different regions of the cell and cAMP responses to 10 μM isoproterenol, 10 μM PGE₁, or 50 μM forskolin were observed. The agonist-induced cAMP responses reached steady plateaus within 4 min, whether the sensors were targeted to the plasma membrane or diffusely distributed to the cytosol. Interestingly, they observed a slow spatial spread of cAMP, consistent with our previous results (28, 31, 32). The differences in the kinetics of the observed responses may have occurred because the membrane localized EPAC sensors traffic to different regions of the plasma membrane than CNG channels, and thus measure a different subcellular pool of cAMP. Another possibility is that the HEK-293 cells used in the study by DiPilato et al. were inherently different. Consistent with the latter possibility, we routinely observe transient isoproterenol-induced cAMP signals using either CNG channel-based sensors or enzyme immunoassays (data not shown); however, the responses presented by DiPilato et al. reached a steady plateau, regardless of the subcellular localization of the EPAC-based sensor. Experiments need to be conducted in the same cells to reconcile potential differences between the responses monitored with different cAMP sensors.

Recently, Rochais et al. (37, 38) used CNG channels to examine cAMP PDE activity in rat cardiac myocytes. They found that exposure of cardiac myocytes to 100 nM isoproterenol triggered a transient cAMP response; however, the decline of the response was slower than those measured in HEK-293 cells. Extracellular application of H89 increased isoproterenol-induced and L-858051 (an analog of forskolin)-induced cAMP signals, as measured by CNG channels, but did not alter isoproterenol- or L-858051-induced stimulation of total cellular PDE3 or PDE4 activities. While the basis for the H89 effects is not fully understood, they were likely due, at least in part, to a PKA-mediated increase in PDE3 or 4 activity at the plasma membrane. They also found that cAMP signals triggered by different hormones were regulated by distinct subsets of PDE families present. The latter observation further implicates compartmentalization as the primary mechanism for the specificity of cAMP signals within cardiac myocytes.

The high resolution measurements of near-membrane cAMP signals presented here have allowed us to develop a plausible mathematical model of the cellular mechanisms underlying these responses. This model can be used to better understand cAMP signals measured in other systems. We have used the model to investigate the roles of PKA, PDE4, and processes such as receptor desensitization in shaping cAMP signals, by altering the concentration (PKA) or kinetics (PDE4 and receptor desensitization) of relevant enzymes. Two interesting predictions can be drawn from these simulations. First, processes such as receptor desensitization may not contribute significantly to the time course of transient cAMP signals if PKA-mediated stimulation of PDE4 activity is present. It remains to be determined if regulation of PDE activity and receptor desensitization act in concert to regulate cAMP signals, or if one process typically dominates the time course of the response. Second, the model predicts that nonuniform concentrations of PKA may buffer cAMP to different extents in different subcellular compartments. Beautiful examples of nonuniform PKA distribution caused by AKAPs are presented in Refs. 26 and 50. AKAPs also help to generate nonuniform concentrations of other proteins, including PDE4 (10, 48). High levels of localized cAMP buffers (e.g., 5 μM PKA) and PDE4 would allow cAMP signals to activate PKA without activating EPAC or native CNG channels. In this scenario, EPAC and CNG channels would be activated after prolonged stimulation of AC (after the buffers had been saturated), or when PDE activity is inhibited. This hypothesis is particularly intriguing given the recent discovery of a signaling complex that contains mAKAP, PKA, PDE4D3, and EPAC1 (9). The measurement of local PKA concentration, as well as the concentration of other proteins within signaling modules, is an important area of future research. Such data are necessary if we are to determine whether localized PKA concentrations do indeed contribute to the segregation of cAMP-mediated cellular responses, and to understand how information is transmitted through the cAMP signaling pathway.