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. 2016 Aug 13;27(9):4411–4422. doi: 10.1093/cercor/bhw243

Adenosine Differentially Modulates Synaptic Transmission of Excitatory and Inhibitory Microcircuits in Layer 4 of Rat Barrel Cortex

Guanxiao Qi 1,*, Karlijn van Aerde 1,5, Ted Abel 2, Dirk Feldmeyer 1,3,4,*
PMCID: PMC6433180  PMID: 27522071

Abstract

Adenosine is considered to be a key regulator of sleep homeostasis by promoting slow-wave sleep through inhibition of the brain's arousal centers. However, little is known about the effect of adenosine on neuronal network activity at the cellular level in the neocortex. Here, we show that adenosine differentially modulates synaptic transmission between different types of neurons in cortical layer 4 (L4) through activation of pre- and/or postsynaptically located adenosine A1 receptors. In recurrent excitatory connections between L4 spiny neurons, adenosine suppresses synaptic transmission through activation of both pre- and postsynaptic A1 receptors. In reciprocal excitatory and inhibitory connections between L4 spiny neurons and interneurons, adenosine strongly suppresses excitatory transmission via activating presynaptic A1 receptors but only slightly suppresses inhibitory transmission via activating postsynaptic A1 receptors. Adenosine has no effect on inhibitory transmission between L4 interneurons. The effect of adenosine is concentration dependent and first visible at a concentration of 1 μM. The effect of adenosine is blocked by the specific A1 receptor antagonist, 8-cyclopentyltheophylline or the nonspecific adenosine receptor antagonist, caffeine. By differentially affecting excitatory and inhibitory synaptic transmission, adenosine changes the excitation–inhibition balance and causes an overall shift to lower excitability in L4 primary somatosensory (barrel) cortical microcircuits.

Keywords: adenosine, A1 receptors, barrel cortex, layer 4, synaptic transmission

Introduction

Adenosine is an important neuromodulator in the brain, and is considered to be a key regulator of sleep homeostasis (Dunwiddie and Masino 2001). Its concentration increases over the course of wakefulness and further following sleep deprivation (Huston et al. 1996; Porkka-Heiskanen et al. 1997, 2000). Adenosine promotes slow-wave sleep through inhibition of arousal centers including the mesopontine tegmentum (Rainnie et al. 1994; Arrigoni et al. 2001), hypothalamus (Morairty et al. 2004; Liu and Gao 2007) and basal forebrain (Alam et al. 1999; Thakkar et al. 2003) as well as thalamocortical systems providing excitatory drive to these centers (Halassa 2011).

Adenosine is formed from the catabolism of ATP and is released directly by both glial cells and neurons (Latini and Pedata 2001). It functions as a signaling molecule that modulates synaptic transmission and neuronal membrane properties through activation of pre- and postsynaptically located high-affinity inhibitory A1 or excitatory A2a G protein-coupled receptors (Chen et al. 2014). In the central nervous system, adenosine is generally an inhibitory neuromodulator; adenosine binding to A1 receptors decreases the intrinsic excitability of glutamatergic (or cholinergic) neurons by increasing postsynaptic inwardly rectifying potassium conductances (Rainnie et al. 1994; Luscher et al. 1997) and suppresses the release of excitatory neurotransmitters by reducing presynaptic calcium influx (Wu and Saggau 1994; Arrigoni et al. 2001). In the hippocampus, the modulation of excitatory transmission by adenosine is dependent on neuronal activity (Mitchell et al. 1993), temperature (Masino and Dunwiddie 1999), and age (Sebastiao et al. 2000). Endogenous adenosine has been shown to have an important role in regulating synaptic transmission (Dunwiddie 1980; Dunwiddie and Diao 1994) and modulating or gating synaptic plasticity in the hippocampus (Dias et al. 2013) and during maturation of the neocortex (Blundon and Zakharenko 2013).

In the primary somatosensory (barrel) cortex of rodents, layer 4 (L4) neurons are the major targets of thalamocortical afferents from the ventroposterior medial nucleus of thalamus (Bosman et al. 2011; Feldmeyer 2012; Feldmeyer et al. 2013). Previous work has shown that thalamocortical excitation of L4 excitatory and inhibitory neurons is down-regulated by presynaptic adenosine A1 receptors in juvenile and adult mouse barrel cortex (Fontanez and Porter 2006; Mateo and Porter 2015). However, the effect of adenosine on the local intracortical synapses between L4 excitatory and inhibitory neurons has not yet been investigated. Due to the unique position of L4 in gating thalamocortical input to the neocortex, studies on the effect of different neuromodulators (e.g., acetylcholine, noradrenaline, and adenosine) on L4 neuronal microcircuitry are important for understanding neocortical function and dysfunction.

Here, using paired patch-clamp recordings in acute slices of rat primary somatosensory (barrel) cortex, we show that adenosine differentially modulates synaptic transmission between distinct types of L4 barrel neurons through activation of pre- and/or postsynaptically located adenosine A1 receptors. Adenosine strongly suppresses excitatory transmission but has only a minor effect on the inhibitory transmission. Therefore, adenosine causes an overall shift to a lower neuronal activity in the L4 barrel microcircuitry. This adenosine-induced reduction of neuronal activity may play an important role in the maintenance of the neuronal energy balance, furthermore, in consolidating memory formation by pruning spurious synaptic connections formed during periods of strong brain activity, for example, during active exploration of the environment.

Materials and Methods

All experimental procedures involving animals were carried out in accordance with the EU Directive 2010/63/EU for the protection of animals used for scientific purposes, the German animal welfare act and the guidelines of the Federation of Laboratory Animal Science Associations (FELASA). The appropriate permissions for sacrificing animals for brain slice experiments were obtained from the Nordrhein-Westfalen Landesamt für Natur, Umwelt und Verbraucherschutz (LANUV).

Slice Preparation

Acute oblique coronal slices (350-μm thick) of the primary somatosensory (barrel) cortex were prepared from postnatal 17–33 (22 ± 4) day-old Wistar rats as previously described (Radnikow et al. 2012). Rats were maintained on a 12-h/12-h light/dark cycle with lights on from 7 AM to 7 PM. Rats were lightly anesthetized with a concentration <0.1% of isoflurane and decapitated between 10:30 AM and 11:30 AM, and brain slices containing the barrel cortex were cut at 45° to the midline in cold extracellular solution using a vibrating microslicer (MICROM HM 650 V, Walldorf, Germany). Slices were incubated at room temperature (22–24 °C) for at least 1 h before use. Slices from animals older than 20 days old were incubated at 33–35°C for 1 h and then gradually cooled down to room temperature.

Solutions

During recording, slices were continuously perfused at 3–5 ml/min with an extracellular solution containing (in mM): 125 NaCl, 2.5 KCl, 25 glucose, 25 NaHCO3, 1.25 NaH2PO4, 2 CaCl2, and 1 MgCl2 (bubbled with 95% O2 and 5% CO2). During slice preparation, the extracellular solution had a composition similar to that of the perfusion solution except for a decreased CaCl2 (1 mM) and increased MgCl2 (4 mM) concentration. The composition of the pipette (intracellular) solution was as follows (in mM): 135 K-gluconate, 4 KCl, 10 HEPES, 10 Pcreatine-Na, and 4 ATP-Mg (adjusted to pH 7.3 with KOH); the osmolarity of the solution was 300 mOsm. Biocytin (Sigma) at a concentration of 5 mg/ml was routinely added to the intracellular solution, and cells were filled during recording. For cell-attached stimulation (see below), we used a pipette solution containing (in mM): 105 Na-gluconate, 30 NaCl, 10 HEPES, 10 phosphocreatine, 4 ATP-Mg, and 0.3 GTP (adjusted to pH 7.3 with NaOH).

Cell Identification

Slices were placed in the recording chamber under an upright microscope (fitted with ×4, 0.13 numerical aperture and ×40, water immersion, 0.80 numerical aperture objectives; Olympus). The barrel field was visualized at low magnification under bright-field illumination and can be identified in L4 as narrow dark stripes with evenly spaced, light “hollows.” Barrel structures were visible in 6–8 slices for each preparation. Individual L4 neurons were identified in the barrel at ×80 magnification using infrared differential interference contrast microscopy. Putative excitatory neurons (spiny stellate cells and star pyramidal neurons) in the barrel had small round or oval somata while putative inhibitory neurons (fast spiking and non-fast spiking interneurons) generally showed large and/or elongated somata.

Electrophysiological Recordings

Whole-cell patch-clamp recordings were made from L4 neurons at 32–33°C using patch pipettes of 5–8 MΩ resistance pulled from thick borosilicate glass capillaries (outer diameter, 2.0 mm; inner diameter 1.0 mm). For connections between excitatory neurons, a searching procedure as described previously (Radnikow et al. 2012; Qi et al. 2015) was adopted. After establishing a synaptic connection, both pre- and postsynaptic excitatory neurons were recorded in whole-cell mode. For connections including fast spiking interneurons, the searching procedure was not necessary due to the high connectivity between fast spiking interneurons and other excitatory neurons (Koelbl et al. 2015) or inhibitory interneurons (unpublished observation). Therefore, two neurons including one fast spiking interneuron were patched randomly in the same barrel. Subsequently, all synaptic connections were tested for reciprocal connectivity; if found postsynaptic potentials were recorded for both directions.

For recordings of excitatory postsynaptic potentials (EPSPs), postsynaptic neurons were held at resting membrane potential and for recordings of inhibitory postsynaptic potentials (IPSPs), postsynaptic neurons were held at −55 mV by injecting a constant positive current to increase the driving force (IPSP reversal potential was calculated to be −85 mV (Koelbl et al. 2015) for the internal and external solution used in this study). Postsynaptic potentials (PSPs) were evoked in the postsynaptic neuron by eliciting two action potentials (APs) in the presynaptic neuron with paired short (5 ms) current pulses (100 ms inter-pulse interval) at a frequency of 0.1 Hz. The series resistance was monitored during recordings. When the series resistance was >40 MΩ or changed by >20%, neurons were excluded from the analysis. Signals were amplified using an EPC10-triple amplifier (HEKA Elektronik), filtered at 2.9 kHz, and sampled at 10 kHz.

Drug Application

Adenosine (1–500 µM), N6-cyclopentyladenosine (CPA) (1 µM, a specific adenosine A1 receptor agonist), 8-cyclopentyltheophylline (CPT) (5 µM, a specific adenosine A1 receptor antagonist), caffeine (1–2 mM, a low-affinity nonspecific adenosine receptor antagonist), Barium (200 µM), and ZD7288 (10 µM) were all bath-applied in the perfusion system. For paired recordings, the first 30–60 PSPs were recorded under control condition. After applying adenosine at different concentrations in the extracellular solution for at least 5 min, 30–60 PSPs were recorded. Finally, after wash-out or co-application of adenosine and its antagonists (CPT or caffeine) for more than 5 min, 30–60 PSPs were recorded. In some experiments, PSPs were continuously recorded during the drug application to determine the time course of changes in PSP properties (e.g., amplitude). Dose–response curves were obtained by applying adenosine at increasing concentrations (1, 10, 50, 100, and 500 µM) sequentially for the same neuron pair. For single-cell recordings, a stable continuous recording of the membrane potential was performed for at least 3 min before adenosine application. After adenosine application recording continued until the membrane potential was stable again. During wash-out, continuous recording was performed until the membrane potential returned to the control level or stabilized at a new equilibrium.

Data Analysis

Acquired data were stored for off-line analysis (Igor; WaveMetrics). PSP amplitude, latency, and kinetics were determined as described previously (Feldmeyer et al. 1999). Briefly, all sweeps were aligned to their corresponding presynaptic AP peaks and averaged to generate the mean PSP. Then, the PSP peak amplitude for each individual sweep was determined within a “peak search window” of 5 ms after the presynaptic AP and averaged over 1 ms. Subsequently, a baseline potential measured within a window of similar duration just preceding the PSP was subtracted. All recordings were inspected visually. The paired-pulse ratio (PPR) was defined as the mean amplitude of the second PSP divided by that of the first PSP elicited by paired APs at 10 Hz. Failures were defined as events with amplitudes <1.5× the standard deviation (SD) of the noise within the baseline window. So as not to misclassify small responses as failures, care was taken to verify that the failure average was zero. The coefficient of variation (CV) was calculated as the SD divided by the mean of PSP amplitude. Passive membrane properties were calculated as follows: the resting membrane potential was measured immediately after establishing the whole-cell recording configuration. The input resistance (Rin) was calculated as the slope of the linear fit to the current–voltage relationship for the current injection from −50 to 50 pA in 10 pA steps. For this relationship, transient membrane potential values were used before some slowly-activating channels (e.g., hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channels) opened. The membrane time constant was obtained by fitting a single exponential function to the membrane potential deflection in response to a −50 pA current injection. The sag was calculated as the percentage of the difference between transient and stable membrane potentials to a hyperpolarization amplitude of −10 mV after injecting a negative current. The rheobase was defined as the minimal current amplitude of 1 s duration that resulted in the first one or two APs. Analysis of spike waveforms was performed on single APs elicited by depolarizing threshold current pulses. Briefly, the AP threshold was defined as the membrane potential where the second derivative of membrane potential exceeds 3× SD of its baseline value before spike generation. The AP amplitude was defined as the difference between peak and threshold membrane potentials. The AP half-width was defined as the spike width at its half amplitude. The amplitude of the afterhyperpolarization (AHP) was defined as the difference between AP threshold and the most negative membrane potential attained during the AHP. For all data, means ± SD are given.

Histological Procedures

After recording, slices were fixed at 4°C for at least 24 h in 100 mM PBS containing 4% paraformaldehyde (pH 7.4). Slices containing biocytin-filled neuronal pairs were processed using a protocol described previously (Marx et al. 2012). Slices were incubated in 0.1% Triton X-100 solution containing avidin-biotinylated horseradish peroxidase (ABC-Elite; Camon); subsequently, they were reacted using 3,3-diaminobenzidine as a chromogen under visual control until the dendritic and axonal arborization was clearly visible (usually after 2–4 min). Slices were dehydrated and then mounted on slides, embedded in Eukitt (Marienfeld Lab. Glassware), and enclosed with a thin coverslip.

Morphological Reconstructions

Biocytin-labeled pairs of neurons were examined under the light microscope. Representative pairs were photographed at low magnification to document the dendritic and axonal arborization. Subsequently, neurons were reconstructed with the aid of Neurolucida software (MicroBrightField) using an Olympus Optical BX61 microscope at a high magnification with a 100-fold oil immersion objective (Marx et al. 2012).

Statistical Analysis

Paired Student's t-test or Wilcoxon signed-rank test (n < 10) was used for statistical comparisons between two groups and one-way ANOVA followed by post hoc Tukey's test for statistical comparisons among multiple groups. The normality of distribution was determined by the Kolmogorov–Smirnov test. Statistical significance was set at P < 0.05; n indicates the number of neurons analyzed.

Results

Neocortical neurons can be divided broadly into two populations: glutamatergic excitatory neurons and GABAergic inhibitory interneurons. Accordingly, there are four synaptic connection types: excitatory–excitatory (E–E) and excitatory–inhibitory (E–I) glutamatergic connections; inhibitory–excitatory (I–E), and inhibitory–inhibitory (I–I) GABAergic connections. The effect of adenosine on these four synaptic connection types was investigated in electrophysiologically and morphologically identified excitatory and inhibitory neurons in L4 of the barrel cortex.

Adenosine Suppresses Synaptic Transmission Between L4 Excitatory Neurons Via Activation of Both Pre- and Postsynaptic A1 Receptors

Paired recordings were made from synaptically coupled L4 excitatory (spiny stellate or star pyramidal) neurons. Both pre- and postsynaptic neurons showed adapting regular spiking firing patterns when depolarized by a suprathreshold current pulse (Fig. 1A). Bath application of adenosine (100 µM) caused a hyperpolarization of the membrane potential of excitatory neurons (Fig. 1B and Supplementary Fig. 1A,B) (van Aerde et al. 2015). In the majority of excitatory neurons the adenosine-induced hyperpolarization of the membrane potential was persistent. However, in some excitatory neurons the membrane hyperpolarization gradually recovered already during the application of adenosine. This may be caused by a deactivation of adenosine receptors or downstream receptor-related channels.

Figure 1.

Figure 1.

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Adenosine suppresses synaptic transmission between L4 excitatory neurons. (A–D) Example recordings from an L4 E–E connection under control and adenosine (100 µM) conditions. (A) Somatodendritic morphologies and firing patterns of pre- (blue) and postsynaptic (green) L4 excitatory neurons. (B) Time course of membrane potential (Vm) changes due to the application of adenosine. (C) EPSPs recorded from the same pair under control and adenosine conditions. Top, presynaptic APs; Middle, five individual EPSPs; Bottom, average EPSPs. (D) Overlay of average EPSPs. (E) Summary data (n = 28) of adenosine-induced changes in several EPSP properties. *P < 0.05, **P < 0.01, ***P < 0.001 for paired Student's t-test. Error bars represent SD.

Other neuronal membrane properties such as Rin also changed following adenosine application both under normal conditions (Table 1 and Supplementary Fig. 1) and in the presence of the HCN channel blocker ZD7288 (Supplementary Fig. 2), resulting in a decreased neuronal excitability. Furthermore, adenosine decreased the voltage sag (Table 1) and the Ih current (Supplementary Fig. 3) in the presence of Ba2+, reflecting an adenosine-induced partial block of HCN channels. Adenosine also suppressed synaptic transmission in E–E connections (Fig. 1C–E). The mean EPSP amplitude decreased from 1.38 ± 1.21 mV to 0.66 ± 0.70 mV (n = 28; P = 2.46×10–6, paired Student's t-test) while the PPR increased from 0.9 ± 0.1 to 1.2 ± 0.4 (n = 28; P = 5.66×10–4, paired Student's t-test). Furthermore, the CV increased from 0.3 ± 0.2 to 0.6 ± 0.2 (n = 28; P = 4.27 × 10–10, paired Student's t-test) and the failure rate (FR) from 9 ± 18% to 29 ± 26% (n = 27; P = 3.59 × 10–5, paired Student's t-test). These changes suggest that adenosine decreases the neurotransmitter release probability via activation of presynaptic adenosine receptors. At the same time, the EPSP decay time constant decreased from 38 ± 15 ms to 19 ± 8 ms (n = 25; P = 1.70 × 10–6, paired Student's t-test), reflecting the activation of postsynaptic adenosine receptors. Other synaptic properties, except for the AP-EPSP latency, were also altered by adenosine (Table 2). The effect of adenosine on E–E connections was reversible after wash-out of adenosine.

Table 1.

Intrinsic membrane properties of L4 neurons under control and 100 µM adenosine conditions

Excitatory (E) Inhibitory (I)
Control
Resting membrane potential (mV) −73.2 ± 6.0 (n = 39) −67.5 ± 3.0 (n = 18)
Input resistance (MΩ) 208.1 ± 63.3 (n = 39) 83.2 ± 18.0 (n = 18)
Time constant (ms) 19.7 ± 6.9 (n = 39) 8.5 ± 1.8 (n = 18)
Sag (%) 11.9 ± 6.1 (n = 39) 7.2 ± 5.7 (n = 18)
Rheobase (pA) 104.1 ± 40.5 (n = 39) 338.9 ± 80.7 (n = 18)
Afterhyperpolarization (mV) 18.8 ± 3.0 (n = 33) 22.7 ± 3.5 (n = 17)
Adenosine
Resting membrane potential (mV) −76.1 ± 6.3** (n = 39) −67.9 ± 2.7 (n = 18)
Input resistance (MΩ) 181.9 ± 50.7** (n = 39) 82.4 ± 22.7 (n = 18)
Time constant (ms) 16.5 ± 5.0** (n = 39) 7.4 ± 1.6 (n = 18)
Sag (%) 3.9 ± 4.4*** (n = 39) 5.4 ± 3.7 (n = 18)
Rheobase (pA) 140.5 ± 47.7*** (n = 39) 366.1 ± 86.8 (n = 18)
Afterhyperpolarization (mV) 16.0 ± 2.5*** (n = 33) 20.9 ± 4.4 (n = 17)
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Bold font indicates significant differences to control; *P < 0.05, **P < 0.01, ***P < 0.001 for paired Student's t-test.

Table 2.

EPSP/IPSP properties of four types of L4 synaptic connections under control and 100 µM adenosine conditions

Excitatory–excitatory (E–E) Excitatory–inhibitory (E–I) Inhibitory–excitatory (I–E) Inhibitory–inhibitory (I–I)
Control
Amplitude (mV) 1.38 ± 1.21 (n = 28) 2.67 ± 2.01 (n = 19) -2.35 ± 2.06 (n = 19) −1.28 ± 0.56 (n = 7)
Paired-pulse ratio 0.92 ± 0.12 (n = 28) 0.94 ± 0.27 (n = 19) 0.84 ± 0.13 (n = 19) 0.78 ± 0.11 (n = 7)
Coefficient of variation 0.33 ± 0.18 (n = 27) 0.29 ± 0.14 (n = 18) 0.31 ± 0.15 (n = 19) 0.28 ± 0.11 (n = 7)
Failure rate (%) 9 ± 18 (n = 27) 1.4 ± 4.8 (n = 18) 6.3 ± 12 (n = 19) 3.7 ± 7.8 (n = 7)
Rise time (ms) 1.76 ± 0.69 (n = 24) 0.49 ± 0.22 (n = 18) 2.19 ± 0.88 (n = 19) 0.84 ± 0.36 (n = 7)
Latency (ms) 1.23 ± 0.31 (n = 24) 0.91 ± 0.20 (n = 18) 0.57 ± 0.26 (n = 19) 0.65 ± 0.12 (n = 7)
Decay time (ms) 37.9 ± 14.8 (n = 25) 9.6 ± 1.7 (n = 17) 35.3 ± 14.6 (n = 19) 12.7 ± 10.6 (n = 7)
Adenosine
Amplitude (mV) 0.66 ± 0.70*** (n = 28) 0.96 ± 0.78*** (n = 19) −2.10 ± 1.96* (n = 19) −1.33 ± 0.50 (n = 7)
Amplitude of control # 0.42 ± 0.20*** (n = 28) 0.36 ± 0.15*** (n = 19) 0.93 ± 0.24* (n = 19) 1.08 ± 0.21 (n = 7)
Paired-pulse ratio 1.17 ± 0.37*** (n = 28) 1.13 ± 0.39* (n = 19) 0.80 ± 0.079 (n = 19) 0.72 ± 0.076 (n = 7)
Coefficient of variation 0.59 ± 0.23*** (n = 27) 0.52 ± 0.18*** (n = 18) 0.29 ± 0.13 (n = 19) 0.23 ± 0.075 (n = 7)
Failure rate (%) 29 ± 26*** (n = 27) 15 ± 19** (n = 18) 3.2 ± 5.8 (n = 19) 1.3 ± 3.4 (n = 7)
Rise time (ms) 1.45 ± 0.50* (n = 24) 0.51 ± 0.17 (n = 18) 1.75 ± 0.56* (n = 19) 0.82 ± 0.29 (n = 7)
Latency (ms) 1.30 ± 0.36 (n = 24) 0.90 ± 0.20 (n = 18) 0.59 ± 0.18 (n = 19) 0.67 ± 0.11 (n = 7)
Decay time (ms) 19.2 ± 7.5*** (n = 25) 9.7 ± 2.9 (n = 17) 22.7 ± 8.0*** (n = 19) 12.3 ± 7.9 (n = 7)
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Bold font indicates significant differences to control; *P < 0.05, **P < 0.01, ***P < 0.001 for paired Student's t-test.

To investigate the effect of adenosine on repetitive synapse stimulation and temporal EPSP summation, a train of ten suprathreshold current pulses at 10 Hz was applied to the presynaptic neurons and ten EPSPs were recorded in postsynaptic neurons (Supplementary Fig. 4A,B). Adenosine had a greater effect in decreasing EPSP amplitudes earlier in the train of EPSPs. Therefore, the short-term plasticity of the EPSP train was switched from on average a strong depression to a weak facilitation. Furthermore, the summation effect was largely removed due to the faster decay time course of EPSPs evoked in the presence of adenosine (Supplementary Fig. 4A).

Previous studies suggested that the A1 receptor is the main adenosine receptor subtype in the neocortex (Yang et al. 2007; Kerr et al. 2013; Wang et al. 2013). To investigate whether the effect of adenosine found in this study is induced by A1 receptor activation, a specific A1 receptor antagonist, CPT (5 µM), was co-applied with adenosine (100 µM) after adenosine had been applied alone. The effect of adenosine on E–E connections was blocked (EPSP amplitude: 1.83 ± 1.64 mV for control; 0.66 ± 0.92 mV for adenosine; 1.68 ± 2.03 mV for adenosine and CPT; n = 7; P = 0.58 for adenosine and CPT vs. control, Wilcoxon signed-rank test; Fig. 2A,B). Co-application of adenosine and CPT did also block the adenosine effect on other EPSP properties (Fig. 2B). Furthermore, application of the specific A1 receptor agonist CPA (1 µM) mimicked the effect of 100 µM adenosine (Fig. 3A).

Figure 2.

Figure 2.

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Adenosine suppresses synaptic transmission between L4 excitatory neurons via activation of both pre- and postsynaptic A1 receptors. (A) Overlay of average EPSPs recorded under control, adenosine, and adenosine & CPT (5 µM) conditions. (B) Summary data (n = 7) showing CPT blockade of adenosine-induced changes. *P < 0.05, **P < 0.01, ***P < 0.001 for Wilcoxon signed-rank test. Error bars represent SD.

Figure 3.

Figure 3.

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Adenosine suppression of excitatory transmission is concentration dependent and was blocked by caffeine. (A) Summary data of relative EPSP amplitude for different drug applications. Inset, overlay of average EPSPs under control and CPT conditions. (B) Overlay of average EPSPs recorded under control, adenosine, adenosine, and adenosine & caffeine conditions. (C) Time course of EPSP amplitude change due to the application of caffeine (0.5–1 mM). Inset, overlay of average EPSPs under control and caffeine conditions. (D) Summary data for caffeine application. *P < 0.05 for Wilcoxon signed-rank test. Error bars represent SD.

The effect of adenosine was concentration dependent and saturated at a concentration of 500 µM with a half-maximal effective concentration of 9.6 µM (Fig. 3A). Furthermore, caffeine (1–2 mM), a nonspecific antagonist of adenosine receptors, was also able to block the effect of adenosine on E–E connections (EPSP amplitude: 0.90 ± 0.72 mV for control; 0.62 ± 0.65 mV for adenosine; 0.87 ± 0.77 mV for adenosine and caffeine; n = 5; P = 0.44 for adenosine and caffeine vs. control, Wilcoxon sighed-rank test; Fig. 3B,D). Tonic suppression of excitatory transmission by endogenous adenosine was revealed by the enhancement of EPSP amplitude after the application of CPT (Fig. 3A) or caffeine (Fig. 3C,D) alone. On the basis of these findings, the concentration of endogenous adenosine in our slice preparation was estimated to be around 1 µM.

Our data show that adenosine suppresses synaptic transmission between excitatory neurons via activation of both pre- and postsynaptic A1 receptors. To address the question whether A1 receptors act via similar ion channels in pre- and postsynaptic compartments, barium (Ba2+, 200 µM), a nonspecific blocker of inwardly rectifying potassium (Kir) channels, was co-applied with adenosine after the adenosine application. Ba2+ blocked the adenosine-induced membrane hyperpolarization in postsynaptic neurons but did not affect the suppression of synaptic transmission by adenosine (Supplementary Fig. 5). This indicates that only the postsynaptic effect of adenosine is directly mediated through Kir channels (Luscher et al. 1997; van Aerde et al. 2015). The A1 receptor-induced reduction in presynaptic neurotransmitter release probability for evoked synaptic transmission is most likely due to a reduced calcium influx through presynaptic voltage-dependent calcium channels as described by Wu and Saggau (1994, 1997) for hippocampal CA3-CA1 synapses, but an exact identification of the presynaptic calcium channel subtype is beyond the scope of this work. On the other hand, adenosine might interfere with calcium release in the presynaptic terminal or directly with the neurotransmitter release machinery via G protein-induced signaling cascades.

In order to investigate whether HCN channels contribute to the adenosine-induced reduction in the release probability, we performed additional experiments in the presence of HCN channel blocker ZD7288. These experiments demonstrate that ZD7288 does not affect the excitatory synaptic transmission (Supplementary Fig. 6).

Adenosine Modulates Excitatory Transmission Via Presynaptic A1 Receptors and Inhibitory Transmission Via Postsynaptic A1 Receptors Between L4 Excitatory and Inhibitory Neurons

In addition to recurrent excitatory synapses, L4 excitatory neurons also form reciprocal connections with neighboring L4 inhibitory (fast spiking, n = 19) interneurons. L4 excitatory neurons showed regular AP firing patterns while the majority of L4 inhibitory interneurons showed high-frequency AP firing patterns (Fig. 4A). In addition, L4 and other cortical layers contain a very heterogeneous population of inhibitory interneurons with adapting, irregular or initial bursting firing patterns. For a subset of those, we demonstrated that adenosine did not affect their passive and active electrical properties (van Aerde et al. 2015). Differentiation of excitatory and inhibitory neurons based on AP firing patterns was confirmed by post hoc morphological identification of dendritic spines. Excitatory neurons have spiny dendrites while inhibitory neurons only have aspiny or sparsely spiny dendrites. Bath application of adenosine (100 µM) had a negligible effect on the membrane potential of inhibitory interneurons, in contrast to the adenosine-induced membrane hyperpolarization in excitatory neurons (Fig. 4B and Supplementary Fig. 7A,B) (van Aerde et al. 2015). Other membrane properties of interneurons were also not changed by adenosine (Table 1 and Supplementary Fig. 7). Excitatory transmission in E–I connections was strongly suppressed; in contrast, the reciprocal inhibitory transmission in I–E connections was only weakly affected by adenosine (Fig. 4C–G). The mean EPSP amplitude of E–I connections decreased from 2.67 ± 2.01 mV to 0.96 ± 0.78 mV (n = 19; P = 7.26 × 10–5, paired Student's t-test) while the PPR increased from 0.9 ± 0.3 to 1.1 ± 0.4 (n = 19; P = 0.02, paired Student's t-test). The CV increased from 0.3 ± 0.1 to 0.5 ± 0.2 (n = 18; P = 2.19 × 10–6, paired Student's t-test) and the FR from 1.4 ± 4.8% to 15 ± 19% (n = 18; P = 0.004, paired Student's t-test), suggesting a reduction in the release probability at this synapse. However, unlike E–E connections, the decay time remained unchanged (9.6 ± 1.7 ms for control; 9.7 ± 2.9 for adenosine; n = 17; P = 0.80, paired Student's t-test) after adenosine application, indicating a lack of a postsynaptic effect of adenosine on E–I connections (Fig. 4C,D,F). Other synaptic properties were also not changed by adenosine (Table 2). Unlike E–I synapses, the IPSP properties of reciprocal I–E connections changed only little after adenosine application (Fig. 4C,E,G). The mean IPSP amplitude slightly but significantly decreased from −2.35 ± 2.06 mV to −2.10 ± 1.96 mV (n = 19; P < 0.05, paired Student's t-test). A similar reduction in IPSC amplitude was obtained when postsynaptic neurons were recorded in the voltage-clamp configuration (Supplementary Fig. 8). Furthermore, the decay time decreased from 35 ± 15 ms to 23 ± 8 ms (n = 19; P = 1.70 × 10–6, paired Student's t-test). The decrease in IPSP amplitude and decay time by adenosine most likely result from a shunting effect due to a decrease in Rin in the postsynaptic excitatory neurons (Table 1 and Supplementary Fig. 1). Synaptic properties related to the release probability at I–E connections were not changed by adenosine (Table 2). The effects of adenosine on both E–I and I–E connections were reversible.

Figure 4.

Figure 4.

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Adenosine differentially modulates excitatory and inhibitory transmission between L4 excitatory and inhibitory neurons. (A–E) Example recordings from a reciprocal L4 E–I and I–E connection under control and adenosine (100 µM) conditions. (A) Somatodendritic morphologies and firing patterns of an L4 regular spiking (RS) excitatory neuron (blue) and an L4 fast spiking (FS) interneuron (green). (B) Time course of membrane potential (Vm) changes following the application of adenosine. (C) E–I EPSPs and I–E IPSPs from the same pair recorded under control and adenosine conditions. Top, presynaptic APs; Middle, five individual E(I)PSPs; Bottom, average E(I)PSPs. (D,E) Overlay of average E–I EPSPs (D) and I–E IPSPs (E). (F,G) Summary data of adenosine-induced changes in several EPSP (n = 19) (F) and IPSP (n = 19) (G) properties. *P < 0.05, **P < 0.01, ***P < 0.001 for paired Student's t-test. Error bars represent SD.

For a train of EPSPs at 10 Hz in E–I connections, adenosine strongly suppressed the first EPSPs but had a smaller effect on subsequent EPSPs (Supplementary Fig. 4C,D). The short-term plasticity was changed in a similar way to that of E–E connections. Adenosine had a minor effect on the IPSP train in I–E connections with only a slight decrease in the temporal summation of IPSPs (Supplementary Fig. 4E,F).

The effect of adenosine on E–I and I–E connections was blocked by co-application of CPT (5 µM) (Fig. 5). These results suggest that similar to E–E connections, adenosine affects synaptic transmission at both E–I and I–E connections via the activation of A1 receptors.

Figure 5.

Figure 5.

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Adenosine modulates excitatory transmission via presynaptic A1 receptors and inhibitory transmission via postsynaptic A1 receptors between L4 excitatory and inhibitory neurons. (A,C) Overlay of average E–I EPSPs (A) and I–E IPSPs (C) recorded under control, adenosine, adenosine, and adenosine & CPT (5 µM) conditions. (B,D) Summary data showing CPT blockade of adenosine-induced changes in EPSPs (n = 9) (B) and IPSPs (n = 7) (D). *P < 0.05, **P < 0.01, ***P < 0.001 for Wilcoxon signed-rank test. Error bars represent SD.

The results described above suggest that adenosine suppresses the excitatory transmission in E–I connections by decreasing glutamate release via the activation of presynaptic A1 receptors. In contrast, adenosine weakly suppresses the inhibitory transmission in I–E connections via the activation of postsynaptic A1 receptors.

For E–E, E–I, and I–E connections, the CV method was adopted for analyzing adenosine-induced synaptic plasticity. In a binomial distribution, the inverse square of the CV (CV−2) = n × p/(1−p) and the mean EPSP amplitude (M) = n × p × q with n, p, q representing the number of release sites, the release probability, and the quantal EPSP amplitude (i.e., the EPSP amplitude induced by the release of a single presynaptic vesicle), respectively. Therefore, when M but not CV−2 changes, this suggests that only the quantal EPSP amplitude q has changed. A change in CV−2 that is relatively larger than that of M indicates that the release probability P has changed, while a similar relative change in both CV−2 and M suggests that the number of release sites n is altered (Faber and Korn 1991). In the majority of excitatory pairs tested, application of adenosine resulted in a greater proportional decrease in CV−2 than in M (Fig. 6), indicating that the suppressive effect of adenosine on synaptic transmission in E–E and E–I connections mainly resulted from a decrease in neurotransmitter (glutamate) release probability mediated by presynaptic A1 receptors.

Figure 6.

Figure 6.

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Scatter plots of the ratio of the inverse squared coefficients of variation (CV−2) versus the ratio of the mean amplitudes before and after adenosine (100 µM) application. The distribution of data points suggests that adenosine suppresses synaptic transmission in E–E (blue) and E–I (green) connections mainly at presynaptic sites.

Adenosine Has No Effect on Synaptic Transmission Between Inhibitory Neurons

To confirm that adenosine affects the synaptic transmission through pre- and/or postsynaptic receptors present on excitatory neurons, we investigated the effect of adenosine on I–I connections. In L4, recurrent inhibitory synapses form between fast spiking interneurons (Fig. 7A). In all of the I–I connections (n = 7) we recorded, adenosine application did not result in any changes of the membrane (Fig. 7B and Table 1) and synaptic properties (Fig. 7C–E and Table 2).

Figure 7.

Figure 7.

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Adenosine has no effect on the synaptic transmission between L4 inhibitory neurons. (A–D) Example recordings from an L4 I–I connection under control and adenosine (100 µM) conditions. (A) Somatodendritic morphologies and firing patterns of pre- (blue) and postsynaptic (green) L4 inhibitory neurons. (B) Time courses of membrane potential (Vm) change due to the application of adenosine. (C) IPSPs recorded from the same pair under control and adenosine conditions. (D) Overlay of average IPSPs. (E) Summary data (n = 7) of adenosine-induced changes in several EPSP properties. All changes induced by adenosine are not significant (n.s.) for Wilcoxon signed-rank test. Error bars represent SD.

Discussion

In summary, our data show that adenosine selectively and specifically modulates synaptic transmission at different synaptic connections in the neuronal microcircuitry in L4 of the barrel cortex. For recurrent excitatory E–E connections, adenosine suppressed synaptic transmission by decreasing neurotransmitter release presynaptically and neuronal excitability postsynaptically. For reciprocal excitatory E–I and inhibitory I–E connections, adenosine suppressed excitatory transmission by decreasing the presynaptic release of neurotransmitter, whereas adenosine had only a minor effect on inhibitory transmission mediated by a decrease in Rin of the postsynaptic neuron. For recurrent inhibitory I–I connections, adenosine had no effect. Therefore, A1 receptors are distributed on both presynaptic axonal terminals and postsynaptic somatodendritic compartments of L4 excitatory neurons (spiny stellate cells and star pyramidal neurons) but not on L4 inhibitory (fast spiking) interneurons as shown in Figure 8.

Figure 8.

Figure 8.

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Schematic summary of proposed presynaptic axonal and postsynaptic somatodendritic locations of A1 receptors on excitatory (spiny stellate or star pyramidal) neurons and inhibitory (fast spiking) interneurons and their effects on intrinsic excitability and synaptic transmission in barrel cortical L4.

Effects of Adenosine on Neuronal Excitability

Adenosine decreased the intrinsic excitability of L4 excitatory neurons by hyperpolarizing the membrane potential and reducing Rin through opening of G protein-coupled Kir channels (Luscher et al. 1997) and/or blocking HCN channels (Rainnie et al. 1994) following the activation of A1 receptors. However, an adenosine effect on membrane properties of L4 fast spiking inhibitory neurons was not found in our study. This implies that no or only very few (not detectable with the techniques used here) adenosine A1 receptors are located in inhibitory interneurons (Rivkees et al. 1995; Ochiishi et al. 1999). Nevertheless, the possibility cannot be excluded that specific subtypes of L4 inhibitory interneurons (e.g., cannabinoid receptor type 1-expressing interneurons) might express adenosine A1 receptors as shown recently in the hippocampus (Rombo et al. 2014).

Effects of Adenosine on Synaptic Transmission

Adenosine suppressed excitatory synaptic transmission but has a minor effect on inhibitory transmission in L4 of the barrel cortex. This is consistent with previous findings in the hippocampus (Kamiya 1991; Lambert and Teyler 1991; Yoon and Rothman 1991) but different from those in subcortical areas, for example, thalamus (Ulrich and Huguenard 1995), striatum (Mori et al. 1996; Centonze et al. 2001), and hypothalamus (Chen and van den Pol 1997; Oliet and Poulain 1999; Xia et al. 2012). In the immature mouse visual cortex, an adenosine-mediated down-regulation of L1 excitatory GABAergic transmission was found (Kirmse et al. 2008). In addition, inhibition of GABAergic synapses by adenosine in immature rat hippocampal CA1 has also been demonstrated (Jeong et al. 2003), suggesting that the adenosine modulation of GABAergic transmission may depend on the development stage. We found no correlation between the effect of adenosine and the age of rats in the present study; however, the age range used here (17–33 postnatal days) is likely to be too limited to see any such effect. It has also been shown that adenosine slightly but significantly reduced GABAergic transmission in layer 5 of the juvenile mouse barrel cortex (Kruglikov and Rudy 2008). In that study, postsynaptic L5 excitatory neurons were recorded in voltage-clamp configuration and IPSCs were measured using paired electrophysiological recordings. Similar to the results on I–E connections reported here, the inhibition of GABAergic transmission by adenosine in that study may be due to a shunting effect induced by the change of postsynaptic membrane properties (Rin) instead of a direct decrease of presynaptic GABA release (Takigawa and Alzheimer 2002; Ilie et al. 2012).

Endogenous Adenosine In Vitro and In Vivo

Endogenous extracellular adenosine concentration has been estimated to be in the range of 165–300 nM during spontaneous sleep-wake cycles in several brain areas of cats using in vivo microdialysis combined with high-pressure liquid chromatography (Porkka-Heiskanen et al. 1997, 2000). Swamy and Venton (2007) used adenosine voltammetry with carbon-fiber microelectrodes and found a basal adenosine concentration of 200 nM. Using a pharmacological approach, Dunwiddie and Diao (1994) estimated from field EPSP measurements in rat hippocampal brain slices that the endogeneous adenosine concentration was in the range of 140–200 nM.

In all studies mentioned above, the endogenous extracellular adenosine concentration was estimated to be in the nanomolar range. However, both microdialysis and carbon-fiber microelectrodes are relatively large compared with the size of the soma. Also, field EPSP measurements sample over a relatively large extracellular volume and are therefore not close to the site of perisynaptic adenosine release. Furthermore, a long superfusion may lead to adenosine wash-out, in particular in more superficial layers. Therefore, these methods are likely to underestimate basal adenosine concentrations at the level of synaptic contacts. Here, using application of the adenosine-antagonists CPT or caffeine in the external solution, tonic activation of A1 receptors by endogenous adenosine was uncovered in the acute slice preparation and an endogenous adenosine concentration of 1 µM was determined. This is consistent with a mean endogenous adenosine concentration of 2 (0.8–4) µM reported in a recent study (Kerr et al. 2013).

In the present study, adenosine at a concentration of 100 µM was bath-applied to measure the effect of adenosine on neuronal membrane properties or synaptic transmission. Although the actual concentration of adenosine in the perisomatic space or the synaptic cleft is probably <100 µM, it is still much higher than the endogenous adenosine concentration of 1 µM. Therefore, the influence of endogenous adenosine on the effect of bath-applied adenosine should be small.

The Role of Adenosine in Modulating Barrel Cortex Function

In cortical L4, adenosine suppresses excitatory thalamocortical input to both L4 inhibitory and excitatory neurons (Fontanez and Porter 2006; Mateo and Porter 2015). In the neocortex, our previous (van Aerde et al. 2015) and present work reveals a more selective role for adenosine in modulating neuronal excitability and neurotransmission. Thus during prolonged wakefulness or following sleep deprivation when levels of adenosine increase, excitatory transmission in cortical L4 will be strongly suppressed due to an increased extracellular concentration of adenosine. At the same time, the intrinsic excitability of L4 excitatory neurons is also reduced by adenosine. These two effects act synergistically to decrease the L4 neuronal spiking activity and its synaptic drive to supragranular (L2/3) and infragranular (L5/6) layers, giving rise to a low firing rate throughout the cortical column and area. This adenosine-induced reduction of excitatory neuronal activity will be most pronounced at the beginning of the sleep cycle and even more so after sleep deprivation. Thus, the selective effect of adenosine on synaptic connections promotes the slow-wave activity in somatosensory cortex and may play a role in the homeostatic regulation of sleep and the functions of sleep.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/

Funding

DFG research group on Barrel Cortex Function (BaCoFun, Fe 472/4–2), the Helmholtz Society (to D.F.) and NIMH R01, MH 099544 (to T.A.). T.A. is the Brush Family Professor of Biology at the University of Pennsylvania.

Supplementary Material

Supplementary Data
Click here for additional data file. (1.4MB, pdf)

Notes

We thank Werner Hucko for the excellent technical assistance, and Jawad Jawadi for Neurolucida reconstructions. Conflict of Interest: None declared.

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