NMDARs in granule cells contribute to parallel fiber-Purkinje cell synaptic plasticity and motor learning

Abstract

Long-term synaptic plasticity is believed to be the cellular substrate of learning and memory. Synaptic plasticity rules are defined by the specific complement of receptors at the synapse and the associated downstream signaling mechanisms. In young rodents, at the cerebellar synapse between granule cells (GC) and Purkinje cells (PC), bidirectional plasticity is shaped by the balance between transcellular nitric oxide (NO) driven by presynaptic N-methyl-D-aspartate receptor (NMDAR) activation and postsynaptic calcium dynamics. However, the role and the location of NMDAR activation in these pathways is still debated in mature animals. Here, we show in adult rodents that NMDARs are present and functional in presynaptic terminals where their activation triggers NO signaling. In addition, we find that selective genetic deletion of presynaptic, but not postsynaptic, NMDARs prevents synaptic plasticity at parallel fiber-PC (PF-PC) synapses. Consistent with this finding, the selective deletion of GC NMDARs affects adaptation of the vestibulo-ocular reflex. Thus, NMDARs presynaptic to PCs are required for bidirectional synaptic plasticity and cerebellar motor learning.

Keywords: Purkinje cells; cerebellum; motor learning; nitric oxide; pre-NMDARs.

Fig. 1.

NMDARs are present and functional in PF varicosities. (A–F) Electron immunohistochemistry reveals the presence of GluN1 and GluN2 on presynaptic sites of PF-PC synapses. NMDAR labeling of profiles presynaptic to dendritic spines with antibodies recognizing GluN2 (A, C, and E) or GluN1 (B and D) subunits. GluN2 (A) or GluN1 (B) subunit immunoperoxidase deposit is detected in the presynaptic element of asymmetric synapses. The presynaptic particles associated with GluN2 (C) or GluN1 (D) antigenic determinants (arrows) are detected at the edge (arrowheads) of the active zone following preembedding immunogold labeling. (E) With postembedding, immunogold labeling GluN2-associated particles are also found at the edge of presynaptic actives zones showing that the access to antigenic determinant was not limited by the cytoskeleton of the presynaptic differentiation. (F) Gold particle quantification of the distance to the edge of the active zone for GluN2: values along the x-axis represent the distance between the edge of the synaptic complex and the nearest immunogold labeling (mean = 100.1 nm [red], median = 50 nm, SEM = 24.3, n = 41), negative values represent particles within the active zone. Note: 82.5% of the gold particles are outside the active zone (right of the dark vertical line). (G–J) Calcium imaging of GCaMP6f-expressing PF varicosities. (G) Acousto-optic deflectors based two-photon snapshot projection (1 plane, 10 images) of a GC expressing td-Tomato. PFs are directly stimulated in the molecular layer (ml), and images are recorded at least at 50 μm from the stimulation point (gcl: granule cell layer, pcl: Purkinje cell layer). Enlarged: varicosity calcium image example before (Top), during (Middle), and after (Bottom) blocking NMDARs (Top to Bottom, respectively). (H) Calcium transient example of another labeled varicosity (25 to 30 PFs stimulations at 200 Hz). Baseline, APV, and Zn²⁺ application, washout, and ([baseline]-[NMDAR blockade]) subtraction (purple dashed). Note the NMDAR-blockade effect on the calcium transient. (I) Time course of the normalized ∆F/F in control conditions (n = 107 varicosities, 31 slices from n = 14 mice). A total of 150 μM D-APV and 300 nM Zn²⁺ were bath applied from minute 8 to 28. (J) Normalized ∆F/F data histogram. Box plot of normalized data comparing the signal in control conditions, during NMDAR block, and after washout (blue). Mean (red dots) and median (red lines) are shown. Statistical significance was tested using Wilcoxon test (***P < 0.001, **P < 0.01).

Fig. 2.

Synaptic plasticity in animals lacking NMDARs in specific neuronal populations. (A) Schematic representation of the strategy used to knock out the GluN1 gene either in cerebellar GCs (GC-GluN1, wt: blue; ko: green) or in PCs (PC-GluN1, wt: red; ko: black). (B and C) Representative recordings before (gray) and after (dashed line) LTP (B) and LTD (C) induction. The colored dots beside the traces are the same as in D–I. (D and E) Time course of the normalized EPSC charge (Top) and PPR (Bottom), in GC-GluN1wt (blue) and GC-GluN1ko (green) for LTP (D) and for LTD (E). (F) Normalized EPSC charge (Top) and PPR (Bottom) after plasticity induction (t = 30 to 35 min) for all individual experiments in GC-GluN1wt (LTP, n = 8 cells; LTD, n = 7 cells) and GC-GluN1ko (LTP, n = 10 cells; LTD, n = 6 cells). (G and H) Time course of the normalized EPSC charge in PC-GluN1wt (red) and PC-GluN1ko (black) for LTP (G) and for LTD (H). (I) Normalized EPSC charge (Top) and PPR (Bottom), after plasticity induction (t = 30 to 35 min) for all individual experiments in PC-GluN1wt (LTP, n = 10 cells; LTD, n = 7 cells) and PC-GluN1ko (LTP, n = 9 cells; LTD, n = 6 cells). PPR was not changed after synaptic plasticity induction (GC-GluN1: D–F, Bottom; PC-GluN1: G–I, Bottom). Boxes represent median (black), the upper, and lower quartile of the distribution. To induce LTP, we use five stimulations at 200 Hz every second, 300 repetitions, while using bursts of two stimulations at 200 Hz every second (300 repetitions) of PFs paired with high-frequency CF burst to induce LTD (see Materials and Methods). Statistical significance was tested using Wilcoxon test (ns: P > 0.05; **P < 0.001).

Fig. 3.

Cerebellum-dependent VOR phase reversal is affected in mice lacking NMDARs in GCs. (A, Top) Schematic representation of the VOR phase reversal experiment. Mice were subjected to a mismatched combination of vestibular and visual input. VOR phase reversal is induced by five 10-min training sessions during which the visual stimulus is rotated in phase with the vestibular input (amplitude, 5°) at increasing amplitudes (day 1, 5°; day 2, 7.5°; day 3 to 4, 10°). (Bottom) VOR phase reversal training typically starting with a decrease of VOR gain (day 1), followed by the increase of the VOR phase (aimed at a phase value of 180°, day 2 to 4) and, when VOR phase is sufficiently reversed, the increase in the VOR gain (day 4). PC-GluN1ko mice show VOR phase reversal with similar phase values as controls (both n = 12 mice) but are impaired in the VOR gain increase after reversal (day 4, P = 0.011). (B) Mice lacking NMDARs from GCs have a more pronounced deficit in that the phase increases more slowly (day 2, 3, and 4: P = 0.001, 0.013, and 0.006, respectively). Note that control littermates of the GC-GluN1 mutant mice appear to adapt their VOR slower than littermates of the PC-GluN1 mutant mice, presumably due to subtle batch and interexperimental differences. (C) VOR phase reversal training also results in an enhanced gain of the OKR. This cerebellum-dependent adaptive change was also impaired in mice lacking NMDARs (n = 11 mice) in GCs (versus 7 control mice, P = 0.045) but not in PC-GluN1ko mice (both n = 11 mice, P = 0.27). (D) VOR gain consolidation, the percentage of learned response present on day 2 (b) relative to the adaptive change on day 1 (a) (see Inset), was not affected in PC-GluN1 mice (P = 0.38, both n = 12 mice, unpaired Student’s t test). In contrast, impaired long-term adaptation could be linked to a deficit in consolidation in GC-GluN1ko mice, compared to controls (P = 0.011, both n = 11 mice, unpaired Student’s t test). (D) Error bars denote SEM (please note that error bars can fall within symbols), *P < 0.05, **P < 0.001.