differential interference contrast
inhibitory postsynaptic currents
spontaneous inhibitory postsynaptic currents
- • Activation of the membrane-binding glucocorticoid receptors enhances spontaneous GABAergic activity and elicits intermittent burst activity in hippocampus and prefrontal cortex of rats.
- • The burst activities are abolished in the presence of tetrodotoxin.
- • The time courses of the effects are different between hippocampus and prefrontal cortex, the onset in the latter being much slower.
- • The nitric oxide (NO) pathway is present and endogenously activated in prefrontal cortex.
- • The effects of membrane-binding glucocorticoid receptor on GABAergic synaptic transmission are mediated by both NO and phospholipase C–diacylglycerol pathways in hippocampus and prefrontal cortex of rats.
Abstract In response to stressor, the brain activates a comprehensive stress system. Among others, this stress system causes release of glucocorticoids that also feed back to the brain. Glucocorticoids affect brain function by activation of both delayed, genomic and rapid, non-genomic mechanisms in rodents. Here we report that application of the potent glucocorticoid receptor agonist dexamethasone (DEX) caused a rapid increase of spontaneous and miniature inhibitory postsynaptic currents (IPSCs) and elicited intermittent burst activities through a non-genomic pathway, involving membrane-located receptors. The onset of the rapid effect in prefrontal cortex (PFC, <15 min) was much slower than in hippocampus (<5 min). The intermittent burst activities were abolished in the presence of TTX. Furthermore, the nitric oxide (NO) pathway was present and endogenously activated in PFC. Part of the rapid DEX effect in PFC remained after blocking NO-sensitive guanylyl cyclase that was due to activation of a phospholipase C–diacylglycerol-dependent signalling pathway. Thus, our data demonstrated that glucocorticoids could rapidly enhance IPSCs and evoke burst activities by activation of at least two different signalling pathways in hippocampus and PFC of rats.
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Stress has a profound time- and region-specific impact on synaptic plasticity and cognitive functions in brain (Maggio & Segal, 2009). Glucocorticoid, as the main stress hormone, activates two receptor types, the high-affinity mineralocorticoid receptor (MR; Type I) and the low-affinity glucocorticoid receptor (GR; Type II; Hwang et al. 2006; Joëls et al. 2008). GRs are widely expressed in the central nervous system with highest densities in cortical regions including prefrontal cortex (PFC), in limbic areas including hippocampus and amygdala, as well as in the thalamus and hypothalamus (Fuxe et al. 1987; Ahima et al. 1991; Cintra et al. 1994; Patel et al. 2000). Glucocorticoids, acting on non-genomic MRs, promote hippocampal excitability and amplify the effect of other stress hormones and contribute to fast behavioural effects after acute stress (Joëls, 2008; de Kloet et al. 2008; Champagne et al. 2009). These non-genomic actions of glucocorticoids may be mediated by membrane-bound receptors (Groeneweg et al. 2011, 2012; Maggio & Segal, 2012) or by the classical intracellular receptors (Karst et al. 2010). The fast effects are complemented later on by slower glucocorticoid receptor-mediated effects which facilitate the recovery from the stressful experience (Joëls et al. 2009). Furthermore, the findings of other labs (Maier et al. 2005; Di et al. 2005, 2009) as well as our recent finding (Hu et al. 2010) have demonstrated that glucocorticoid can also activate membrane-binding non-genomic GRs (nGRs) that transduce rapid non-genomic, G-protein-coupled effects, causing changes of synaptic transmission within short time scales. These recent findings not only completely change our current view of the effects of GR, but also force us to reconsider our current understanding about the related intracellular signalling pathways and the role of the fast action of glucocorticoids in neuronal networks (Groeneweg et al. 2011, 2012).
The PFC region has extensive connections with the thalamus and basal ganglia as well as with the limbic areas (Uylings et al. 2003). Of particular importance is the afferent input from the midline thalamic nuclei, the amygdala, ventral hippocampus and subiculum to ventral PFC areas, through which subcortical limbic information is conveyed to the PFC. By computing the afferent inputs, the further processing of subcortical limbic information within the PFC circuits results in direct modulatory outputs to amygdala–hypothalamic circuits and numerous brainstem areas, and thus, controls the regulation of physiological and emotional responses (Bandler et al. 2000). Chronic stress leads to changes in the afferent inputs from hippocampus that depress the activity of the PFC and enhance the activity of the amygdala–hypothalamic circuits, and cause stress-related emotive responses (Cerqueira et al. 2007). Thus, the PFC plays a pivotal role in the central processing pathway from environmental information to regulation of socio-affective and viscero-motor behaviours (Damasio et al. 2000). Malfunction of the interconnectivity in the PFC circuits would thus substantially contribute to the pathogenesis of mental illness (Bremner, 1999).
In contrast to the detailed studies of long-term, gene-regulation-related genomic effects of glucocorticoids (de Kloet et al. 1998; Joëls et al. 2009), much less is known about the fast effects of glucocorticoids on membrane-binding nGRs, especially in PFC (Groeneweg et al. 2011, 2012). Specifically, we do not know much detail about what happens within the first 60 min after exposure to glucocorticoids. Also, less is known about which signalling pathways are involved in the activation of nGRs in PFC. In the current study, we investigated the intracellular signalling pathways of the membrane-binding, non-genomic GRs in PFC of rats. Our data demonstrated that the rapid effect of glucocorticoid caused an enhancement of GABAergic transmission and evoked phasic burst activities in PFC. This effect was at least partly independent of the activation of the NO-related pathway, but involved a phospholipase C–diacylglycerol (PLC–DAG)-dependent signalling pathway.
All experiments were performed on adult male Sprague–Dawley rats (Harlan Winkelmann, Borchen, Germany) weighing 170–200 g at the beginning of the experiment. All rats were purchased, maintained and mated in the animal facility of Münster. The experiments were performed in accordance with the European Communities Council Directive (86/EEC), and were approved by the Federal State Office for Consumer Protection and Food Safety of North Rhine-Westphalia, Germany.
Animals were anaesthetized with isoflurane and killed by decapitation. Brains were quickly removed and transferred to ice-cold oxygenated (95% O2, 5% CO2) preparation solution containing (in mm): 124 sucrose, 3 KCl, 1.3 MgSO4, 1.24 NaH2PO4, 2.4 CaCl2, 26 NaHCO3, 10 glucose. Acute coronal PFC and hippocampal slices (300 μm) were cut with a vibratome from brains of rats. The acute slices were transferred into incubation chambers with 32–34°C warm oxygenated ACSF containing (in mm): 125 NaCl, 2.5 KCl, 1.25 Na2HPO4, 2 MgSO4, 26 NaHCO3, 1.5 CaCl2, 1 ascorbic acid, and 14 glucose (pH 7.4, aerated with 95% O2, 5% CO2) for a 1 h recovery period, and then kept at room temperature for whole-cell patch-clamp recordings.
The spontaneous inhibitory postsynaptic currents (sIPSCs) were recorded from hippocampus CA1 or PFC neurons at a holding potential of −70 mV. 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX; 10 μm), dl-2-Amino-5-phosphonopentanoic acid (DL-AP5; 50 μm) and strychnine (2 μm) were present to block glutamate and glycine receptor-mediated synaptic currents. The miniature IPSCs (mIPSCs) were recorded in the presence of tetrodotoxin (TTX; 0.5 μm). The recording pipettes were filled with solution containing (in mm): 140 KCl, 1 CaCl2, 10 EGTA, 2 MgCl2, 0.5 Na2-GTP, 4 Na2-ATP, and 10 Hepes (pH was adjusted to 7.2 with KOH).
In slices of hippocampus, all recordings were performed on pyramidal neurons in CA1 as described previously (Hu et al. 2010). In slices of PFC, all recordings were conducted in layer 2/3 of the prelimbic cortex and the recorded neurons were identified by their morphologies under infrared differential interference contrast (IR-DIC) visualization. Here, interneurons were small cells with round or oval cell bodies, whereas the pyramidal neurons were larger cells with triangular soma and pia-oriented apical dendrites, as described previously (Gao, 2007).
The membrane currents were filtered by a four-pole Bessel filter at a corner frequency of 2 kHz, and digitized at a sampling rate of 5 kHz using the DigiData 1322A interface (Axon Instruments/Molecular Devices, Sunnyvale, CA, USA). Data acquisition was performed using commercially available software (pCLAMP 10.1; Axon Instruments/Molecular Devices). MiniAnalysis 6.0.9 (Synaptosoft, Decatur, GA, USA) was used to perform amplitude and frequency analysis of sIPSCs and mIPSCs.
Water-soluble forms of the steroids dexamethasone (DEX) (Sigma Aldrich, St Louis, MO, USA), and DEX–bovine serum albumin and corticosterone–bovine serum albumin conjugates (DEX–BSA or Cort–BSA; purified to remove free steroids by the supplier; Steraloids, Newport, RI, USA) were directly dissolved in ACSF to final concentrations and applied in the bath perfusion up to 60 min. For determining the downstream signalling pathway, the NO donor S-nitroso-N-acetylpenicillamine (SNAP; Tocris), a selective inhibitor of NO-sensitive guanylyl cyclase, as well as 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ; Tocris), the PLC inhibitor U 73122 (Tocris, Germany) and DAG inhibitor RHC 80267 (Tocris) were used in the presence of DEX–BSA.
All non-normally distributed data are expressed as median and confidence intervals. All other data are expressed as means ± SEM. In most experiments, the effects of DEX were tested in four different time phases, where data were averaged over: (a) phase I (control phase): 3 min before drug application; (b) phase II (immediate phase): 1–5 min after drug; (c) phase III (intermittent phase): 10–20 min after drug, and (d) phase IV (late phase): 40–60 min after drug, both in hippocampus and in PFC. Statistical comparisons of electrophysiological data were performed using the non-parametric Mann–Whitney test. Probability values <0.05 were considered significant for all comparisons.
DEX induced spontaneous intermittent IPSC bursts in hippocampus and PFC of rats
All recordings were performed on pyramidal neurons in CA1 (Hu et al. 2010) and on pyramidal neurons in layer 2/3 of the prelimbic cortex. The recorded neurons were identified by their morphologies under infrared differential interference contrast (IR-DIC) visualization as described previously (Gao, 2007). Bath application of the selective glucocorticoid receptor agonist dexamethasone (DEX, 25 nm) caused an overall strong decrease of the inter-event intervals (Fig. 1C and D; hippocampus: control, vs. DEX, P < 0.001; PFC: control vs. DEX, P < 0.001), but minor changes in amplitude of spontaneous IPSCs in hippocampus (Fig. 1C; control vs. DEX, P < 0.05) and in PFC (Fig. 1D; control vs. DEX, P < 0.05) as shown previously in hippocampus of rats (Hu et al. 2010). In addition to the overall enhancement of sIPSCs, aggregations of high frequency IPSC events occurred intermittently in the presence of DEX both in hippocampus and PFC of rats (Fig. 1A and B). The intermittent aggregations of IPSC events can be characterized by a very high frequency (>10 Hz; much higher than the averaged sIPSC frequency of 6 Hz) and a duration of more than 1.5 s. They will be referred to as spontaneous intermittent IPSC bursts (Popescu et al. 2010). Moreover the appearance of the DEX-elicited IPSC bursts differed between hippocampus and PFC in several aspects. First, the averaged burst duration was significantly longer in hippocampus (3.6 ± 0.3 s) than in PFC (1.9 ± 0.1 s; P < 0.001, n = 6; Fig. 1E). Second, the burst incidence, evaluated as the number of bursts that occurred within 60 min, was significantly lower in PFC (11.3 ± 1.6 bursts h−1) than in hippocampus (37.6 ± 5.4 bursts h−1, P < 0.001, n = 6, Fig. 1F). Third, the first burst occurred in less than 5 min after DEX application in hippocampus (time to first burst; 2.1 ± 0.6 min), whereas it took much longer for the first burst to occur in PFC (14.1 ± 1.1 min, P < 0.001, n = 6, Fig. 1G).
Thus, although DEX showed rapid enhancing effects on IPSCs in PFC, these effects differed from those observed in hippocampus, suggesting different underlying cellular mechanisms that need to be further characterized.
Different time courses of DEX-induced facilitation of GABAergic transmission in hippocampus and PFC
To further characterize the time course, we analysed the effects of DEX on overall GABAergic transmission in four different time phases, while the IPSC bursts were excluded from the analysis. Here, data were averaged over: (a) 3 min before drug application (control phase, I), (b) 1–5 min after drug (immediate phase, II), (c) 10–20 min after drug (intermittent phase, III), and (d) 40–60 min after drug (late phase, IV), both in hippocampus and in PFC. Previous reports have demonstrated that the glucocorticoid action affected hypothalamic excitatory transmission (Di et al. 2005) and GABAergic inhibitory transmission within 5 min in hippocampal pyramidal neurons (Hu et al. 2010). In the present study, bath application of 25 nm DEX showed a rapid effect on sIPSC frequency within 5 min in hippocampus neurons (Fig. 2B, control vs. immediate phase, P < 0.001, n = 7), while it increased the amplitude of IPSCs at the same time (Fig. 2B, control vs. immediate phase, P < 0.001, n = 7). Both effects remained until the end of the recording (late phase, 40–60 min; Fig. 2B). Under the same experimental conditions, DEX showed no significant effect on GABAergic transmission in PFC in the immediate phase (Fig. 2C; control vs. immediate phase, n.s., n = 6), but it significantly enhanced the frequency of sIPSCs in the following phases (Fig. 2C; control vs. intermittent phase, P < 0.001, n = 7; late phase, P < 0.001, n = 7). In all cases, the amplitudes of sIPSCs were successively increased after application of DEX in a time-dependent manner (Fig. 2C, right panel).
Thus, DEX facilitated the GABA release and elicited IPSC bursts in both hippocampus and PFC, but the effects showed different time courses. In hippocampus, the effect of DEX on the IPSC frequency had already started in the immediate phase, whereas this effect of DEX became apparent in the intermittent phase in PFC. The effects on the amplitude of IPSCs were similar in hippocampus and PFC. In both, the effects remained until the end of the recording (late phase, 40–60 min; Fig. 2B and C).
DEX facilitates GABAergic transmission via activation of non-genomic membrane-binding glucocorticoid receptors
To test whether the different effects of DEX in hippocampus and PFC were due to activation of membrane-binding nGRs, we performed the above experiments using a membrane-impermeable DEX–BSA conjugate (Maggio & Segal, 2009; Hu et al. 2010). Bath application of DEX–BSA (250 nm; Hu et al. 2010) increased the sIPSC frequency in hippocampus neurons, the time course being similar to that shown before (Fig. 2E; control vs. immediate phase, P < 0.001, n = 7). This effect lasted until the late phase (Fig. 2E; control vs. intermittent phase, P < 0.001, n = 7; late phase, P < 0.001, n = 8), while it caused a minor, but significant effect on the amplitude of IPSCs (Fig. 2E, right panel). In PFC, the effect of DEX–BSA on GABAergic transmission began in the intermittent phase (Fig. 2F; control vs. immediate phase, n.s., n = 6; intermittent phase, P < 0.001, n = 6; late phase, P < 0.001, n = 6). In all cases, the amplitudes of sIPSCs were significantly increased after application of DEX–BSA (Fig. 2F, right panel). It is worth noting that, in contrast to DEX application, the effects of DEX–BSA reached their maximum in the late phase, especially in hippocampus (cf. Fig. 2B and E), possibly due to different pharmacokinetics of DEX and DEX–BSA (Maggio & Segal, 2009; Hu et al. 2010).
In hypothalamus, endogenous IPSC burst activity could be recorded in the presence of TTX suggesting a spike-independent, but Ca2+-dependent, synchronized GABA release (Popescu et al. 2010). To further test whether DEX-elicited burst activity (Fig. 1) was spike dependent, we repeated the above experiments in the presence of TTX (0.5 μm). In the presence of TTX, application of DEX–BSA (250 nm) enhanced the frequency with a similar time course to before (Figs 1 and 2), but not the amplitude of miniature IPSCs, either in hippocampus (Fig. 3B) or in PFC (Fig. 3C), suggesting a presynaptic effect of DEX in pyramidal neurons. Furthermore, the DEX-elicited IPSC burst activities disappeared in the presence of TTX (data not shown), suggesting that DEX-elicited IPSC bursts are dependent on the generation of action potentials (Popescu et al. 2010).
To further verify whether activation of membrane-binding GR might cause the enhancement of IPSCs in hippocampus and PFC, we performed additional experiments using the membrane-impermeable corticosterone–BSA conjugate (Cort–BSA, 100 nm) in the presence of the MR receptor antagonist spironolactone (100 nm; Karst et al. 2005). Application of Cort–BSA showed significant effects on the frequency and amplitude of GABAergic transmission in hippocampus neurons (Fig. 3E) with a time course similar to that recorded using DEX–BSA (Fig. 2E), the effect remaining for more than 40 min (Fig. 3E). On the other hand, application of Cort–BSA showed no significant effect on GABAergic transmission in PFC in the immediate phase, but it significantly enhanced the frequency of sIPSCs in the subsequent phases (Fig. 3F, left panel). In addition, it significantly increased the amplitude of sIPSCs in PFC in the immediate phase (Fig. 3F, right panel).
Taken together, application of DEX, DEX–BSA and Cort–BSA showed very similar effects and time courses within the same brain areas, suggesting that the effects were consequences of activation of membrane-binding nGRs. In addition, the different time courses in hippocampus and PFC suggested that different signalling pathways might be involved.
DEX–BSA-evoked facilitation of GABAergic transmission is not mediated by retrograde NO signalling in PFC
We have previously shown that the activation of nGRs facilitates the GABA release via a NO signalling pathway in hippocampus (Hu et al. 2010). We therefore first tested whether activation of the NO pathway would have same effect in PFC as shown previously in hippocampus (Hu et al. 2010). Bath application of the NO donor S-nitroso-N-acetylpenicillamine (SNAP; 100 μm) caused an increase of frequency of sIPSCs within 5 min in PFC neurons (Fig. 4A and B, control vs. SNAP, P < 0.001, n = 6), but showed no effects on the amplitude of sIPSCs (Fig. 4B, right panel). This result suggested that activation of the NO pathway using the NO donor SNAP would only increase the frequency of GABAergic IPSCs in PFC; this was quite different from what had previously been shown in hippocampus of rats (Hu et al. 2010).
We next tested whether nGR-mediated activation of the NO-dependent pathway would affect the GABAergic transmission in PFC (Hu et al. 2010). In acute slices of PFC, ODQ (50 μm; Hu et al. 2010), a selective inhibitor of NO-sensitive guanylyl cyclase, was incubated for 60 min before the sIPSC frequencies were recorded. It is quite striking that, in the presence of ODQ, the frequency (control, Fig. 4D, left panel; 3.8 ± 0.2 Hz) of sIPSCs was significantly lower than the control frequency before ODQ (control, Fig. 2C: 7.9 ± 0.2 Hz; Fig. 2F: 6.9 ± 0.2 Hz), while the amplitude was quite similar to that before ODQ, indicating that the NO pathway is endogenously activated, and this enhanced the frequency of GABAergic transmission in PFC, but not in hippocampus (Hu et al. 2010).
Similar to the previous results (Fig. 2F), application of DEX–BSA (250 nm) after ODQ incubation showed no significant effect in the immediate phase (Fig. 4C and D; control vs. immediate phase, n.s., n = 7). However, in the intermittent and late phases, DEX–BSA significantly increased sIPSC frequency (Fig. 4C and D; control vs. intermittent phase, P < 0.001, n = 7; late phase, P < 0.001, n = 7), whereas it only showed a significant effect on the amplitude of sIPSCs in the late phase (Fig. 4D, right panel). It is remarkable that, although DEX–BSA showed a similar effect on sIPSC frequency in the presence of ODQ (Fig. 4D), the maximal effect of DEX in the late phase was much weaker in the presence of ODQ (Fig. 4D) than before (Fig. 2C). Thus, the above data suggest that more than 50% of the DEX effect was NO dependent, while a minor part of the effect was NO independent in PFC, probably mediated by other signalling pathways.
DEX–BSA facilitates GABAergic transmission by activation of a PLC–DAG-dependent pathway in PFC
It has been previously demonstrated that the effect of nGR on synaptic transmission could be abolished by blocking postsynaptic G-protein activity (Karst et al. 2010). We next tested the involvement of the PLC–DAG-related pathway (Jung et al. 2005; Choi et al. 2005). The PFC slices were first incubated with a selective antagonist of PLC, U 73122 (50 μm), for 30 min. Thereafter, additional application of DEX–BSA had no significant effect on the frequency and amplitude of sIPSCs within the next 60 min (Fig. 5A and B; n.s., n = 10).
Next, we repeated the same experiment in the presence of a selective inhibitor of DAG, RHC 80267 (50 μm). Similarly, additional application of DEX–BSA had no significant effect on frequency and amplitude of sIPSCs in PFC within the next 60 min (Fig. 5C and D; n.s., n = 6).
Taken together, these results suggested that glucocorticoid exerted its non-genomic effect on GABAergic synaptic transmission in PFC of rats, at least partly, by activation of a PLC–DAG-dependent pathway, the effect being slower than NO-mediated effects in hippocampus (Hu et al. 2010).
To the best of our knowledge, this is the first study that examines the rapid effect of nGRs in prelimbic cortex of rats. Our novel findings were as follows: (1) the selective agonist of glucocorticoid receptor DEX enhanced the spontaneous GABAergic IPSCs and elicited intermittent burst activities in hippocampus and PFC of rats; (2) these effects were mediated by the activation of membrane-binding nGRs as DEX–BSA and Cort–BSA showed the same effects; (3) the DEX-elicited IPSC bursts were abolished in the presence of TTX; (4) the time courses of the DEX effects were different between hippocampus and PFC, the onset in the latter being much slower; (5) the NO pathway was present and endogenously activated in PFC; (6) the effect of DEX on GABAergic synaptic transmission in PFC was at least partly mediated by the activation of a NO-independent, but PLC–DAG-dependent signalling pathway. These data suggested that glucocorticoid could activate nGRs and mediate rapid effects in hippocampus and PFC involving at least two different signalling pathways.
The present study demonstrated that, on top of its effect on tonic IPSCs, DEX also elicited intermittent IPSC bursts, both in pyramidal neurons of hippocampus and PFC (Fig. 1). In hypothalamus, IPSC burst activity could be recorded in the presence of TTX. The authors concluded that an increased presynaptic release of Ca2+ caused such a network-independent, but Ca2+-dependent, synchronized GABAergic burst activity (Popescu et al. 2010). In the present study, the nGR-elicited IPSCs bursts were abolished after application of TTX, suggesting that these IPSC bursts were spike- and network-dependent events. It is quite possible that activation of nGRs on presynaptic terminals enhances the tonic release of GABA from GABAergic interneurons to pyramidal neurons as suggested before (Hu et al. 2010). Furthermore, activation of nGRs expressed on the soma of GABAergic interneurons increases the firing rate of these interneurons and causes spike-dependent IPSC bursts in pyramidal neurons of hippocampus and PFC.
Stress activates the hypothalamic-pituitary-adrenal axis that results in an increased release of corticosteroids from the adrenal glands in all animals. The corticosteroids could mediate a slow genomic effect (de Kloet et al. 1998; Joëls et al. 2009), but also activate rapid non-genomic G-protein-coupled mechanisms (Di et al. 2005; Karst et al. 2005; Joëls et al. 2009; Hu et al. 2011). So far, several different signalling pathways are involved in corticosteroid-mediated rapid effects (Groeneweg et al. 2011, 2012). In hypothalamus, corticosterone elicited rapid effects on excitatory and inhibitory transmission through endocannabinoid- and NO-mediated signalling pathways, respectively (Di et al. 2005, 2009). In amygdala, corticosterone activated a G-protein s (Gs)-mediated mechanism that enhanced endocannabinoid release, and facilitated the consolidation of aversive memories (Campolongo et al. 2009). In hippocampus, corticosterone enhanced glutamate release and increased neuronal excitability through a non-genomic MR-mediated pathway (Karst et al. 2005). Our data demonstrated that glucocorticoids could rapidly affect the function of cortical inhibitory networks by activation of at least two different signalling pathways, being predominantly the NO-mediated pathway in hippocampus (Hu et al. 2010) and, additionally, the G-protein q (Gq)–PLC–DAG-mediated pathway in PFC in the present study. In our opinion, there are several possibilities that might explain the diversity in the glucocorticoid-mediated rapid signalling. First, glucocorticoid can activate different signalling pathways by interacting with nMRs (Karst et al. 2005, 2010) and nGRs (Di et al. 2005, 2009; Hu et al. 2010). Second, the membrane-binding receptors involved can be located on both pre- or postsynaptic sides (Olijslagers et al. 2008), as well as on somatic or dendritic sites, and thus activate different signalling pathways. Third, it is quite possible, that different subtypes of nMR and nGR are expressed in projection neurons and interneurons of hippocampus and PFC that involve different signalling pathways (Groeneweg et al. 2011, 2012). Finally, in the presence of ODQ, the frequency of sIPSCs was much lower (Fig. 4D) than in control (Figs 2 and 3) in the present study, indicating that the NO pathway was tonically activated in PFC, but not in hippocampus (Hu et al. 2010). It is therefore quite reasonable that, due to the tonic activation of the NO pathway, nGR-mediated release of NO will not show an additional effect in PFC. In this case, the effect of nGR-mediated additional activation of the PLC–DAG-related pathway comes to the fore, whereas the NO-mediated effect predominates in hippocampus (Hu et al. 2010).
In the present study, we directly compared the effects of DEX and its membrane-impermeable conjugates DEX–BSA and Cort–BSA in hippocampus and PFC under the same experimental conditions. We demonstrated that although DEX, DEX–BSA and Cort–BSA showed similar effects on GABAergic transmission, there were consistent differences in the time courses of effects, between DEX and the BSA-conjugated compounds as well as between hippocampus and PFC. As described in the Methods, the current study focused on pyramidal neurons in CA1 of hippocampus and in layer 2/3 of prelimbic cortex of rats that were identified solely on DIC and topographical location without further morphological characterizations (Gao, 2007). Therefore, we could not exclude the possibility that a few of the tested neurons might be other types of neurons.
In the present study all drugs were applied by bath application using a perfusion system. Therefore, under the same experimental conditions, the diffusion rate of the drug within the brain slice (300 μm thick) determines the time course of its effect. As the BSA-conjugated compounds are lipophilic and molecularly bigger than DEX itself, the slower diffusion rate of the BSA-conjugated compounds within the brain slices might explain the difference in the time courses of the effect between DEX (Fig. 2B) and DEX–BSA (Fig. 2E) or Cort–BSA (Fig. 3E), similar to reports by other authors (Strehl et al. 2011).
In hippocampus, the effects of DEX, DEX–BSA and Cort–BSA emerged within the first 5 min after drug application (immediate phase: <5 min, cf. Figs 2–4), similar to previous reports (Hu et al. 2010). In contrast, the onset of the effects of DEX, DEX–BSA and Cort–BSA became apparent in the intermittent phase after the drug application in PFC (10–15 min). In both brain areas, the effects of DEX, DEX–BSA and Cort–BSA lasted until the end of the recording (60 min; Figs 2–4). As we never recorded for longer than 60 min in both cases, we could not exclude the possibility that the DEX effect, as shown in the present study, might last beyond 60 min. Thus, the effects in hippocampus (Hu et al. 2010; Figs 2 and 3) and PFC (Figs 2–4) were substantially different to the time course of the DEX effect described by Maggio & Segal (2009). These authors reported that DEX causes an increase in the amplitude of sIPSCs in dorsal hippocampus of the rat that became apparent 30–45 min after DEX application (comparable to late phase: 40–60 min in the current study), suggesting the involvement of genomic GRs. On the other hand, although the onset of the effect of DEX was different between the reported data (Maggio & Segal, 2009; Hu et al. 2010) and the data of the present study (Figs 2 and 3), the total effective time window of DEX action was somehow overlapping (>30 min after drug application). In our opinion, the different onsets of the DEX effect might directly reflect the predominance of different signalling pathways in hippocampus and PFC (see discussion above). It is thus quite plausible that nGR activates the NO pathway and subsequently also a PLC–DAG pathway, both in hippocampus and PFC. The tonic activation of the NO pathway in PFC conceals the effect of nGR-mediated additional release of NO, so that the effect of the subsequent activation of the PLC–DAG pathway predominates in PFC, while the NO effect comes to the fore in hippocampus (Hu et al. 2010).
Furthermore, we speculate that the overlapping time window of the DEX effect might represent the net effect in the transition phase between the activation of fast nGRs and slow GRs (Maggio & Segal, 2009). Although little is known about such transition phases, the difference in time course between the effect of DEX (Fig. 2; can activate both nGR and GR) and DEX–BSA and Cort–BSA (Figs 2 and 3; can activate only membrane-binding nGR) might also be interpreted as differences in such a transition phase.
We have previously shown that chronic stress impaired rhythmic sIPSCs originating from the parvalbumin-positive neurons (Hu et al. 2010). Such functional deficit of cortical interneurons would lead to altered oscillation in the networks (Hu et al. 2010), which has been suggested as an underlying mechanism in working memory deficits in schizophrenic patients (Lewis et al. 2005). On the other hand, our previous data showed that the effect of acute stress on the occurrence of sIPSCs could be partially mimicked by DEX application to control slices, both acute stress and DEX increasing the frequency of sIPSCs to a similar extent (Hu et al. 2010). There, the animals in the acute stress group were subjected to restraint for 30 min. This type of stress response involves the release of various other ‘stress mediators’ that act in concert along with corticosterone. It is thus most likely that an acute stress response collectively involves fast nGR action as well as genomic GR actions that emerge after 30 min of stress exposure. The cellular effect in cortical networks after acute stress would represent the net effect of all actions, including the above-mentioned transition phase. In the present study, we demonstrated that, in addition to its effect on tonic spontaneous IPSCs, the acute activation of nGRs caused increased intermittent GABAergic burst activity both in hippocampus and in PFC (Fig. 1). It is quite plausible that such changes in phasic activation of the inhibitory network would also occur after stress and lead to altered γ-oscillation in the networks (Hu et al. 2010). Thus, although the effects of both acute and chronic stress are much more complex and more comprehensive than the only actions of glucocorticoids, the activation of nGRs and GRs and the transition phase in between would substantially contribute to the development of the final picture of stress-mediated effects. Considering the vital role of synaptic inhibition in the regulation of network oscillations (Somogyi & Klausberger, 2005; Sohal et al. 2009), the glucocorticoid-mediated alteration of phasic inhibitory burst activities may result in changes of network oscillations and thus contribute to changes in working memory and other cognitive function that are common in patients with stress-related psychiatric illnesses (Freund & Katona, 2007).
Z.T. and M-y.Z. performed the experiments. Z.T., M-y.Z., M-g.Z. and W.Z. analysed the data. W.Z. designed the research and wrote the manuscript. All authors approved the final version for publication, and the work was performed at the University of Münster.
This work was supported by Deutsche Forschungsgeme inschaft (SFB TRR58 TP-A08 to W.Z.).
We thank Ch. Schettler for excellent technical assistance. We also thank all members of the laboratory of molecular psychiatry for helpful discussions.