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Stepwise molecular specification of excitatory synapse diversity onto cerebellar Purkinje cells

Nature Neuroscience volume 28, pages 308–319 (2025)Cite this article

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Abstract

Brain function relies on the generation of a large variety of morphologically and functionally diverse, but specific, neuronal synapses. Here we show that, in mice, the initial formation of synapses on cerebellar Purkinje cells involves a presynaptic protein—CBLN1, a member of the C1q protein family—that is secreted by all types of excitatory inputs. The molecular program then evolves only in one of the Purkinje cell inputs, the inferior olivary neurons, with the additional expression of the presynaptic secreted proteins C1QL1, CRTAC1 and LGI2. These molecules work in concert to specify the mature connectivity pattern on the Purkinje cell target. These results show that some inputs actively and gradually specify their synaptic molecular identity, while others rely on the ‘original molecular code’. Thus, the molecular specification of excitatory synapses, crucial for proper circuit function, is acquired in a stepwise manner during mouse postnatal development and obeys input-specific rules.

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Fig. 1: PC excitatory inputs are characterized by different surfaceome expression dynamics during postnatal development.
Fig. 2: Several cell surface proteins control the establishment of CF/PC connectivity.
Fig. 3: A combination of secreted proteins orchestrates CF/PC synaptogenesis.
Fig. 4: CBLN1 from IONs promotes CF/PC connectivity at early stages.
Fig. 5: ION activity shapes CF/PC connectivity and molecular identity.

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Data availability

All data are available in the main text or the Supplementary Information. Single-cell expression data in cerebellar GCs are available at https://apps.kaessmannlab.org/sc-cerebellum-transcriptome/. AlphaFold structure predictions are available on the database (https://alphafold.ebi.ac.uk/). Information on the Kir2.1 channel is available at https://channelpedia.epfl.ch/wikipages/42/. Source data are provided with this paper—statistical source data for figures and extended data figures, and raw image for Extended Data Fig. 5.

Code availability

Plugins are available on GitHub via the following links: custom-made plugin for unbiased 3D detection of individual RNA puncta and DAPI nucleus (https://github.com/orion-cirb/RNA_Scope); custom-made plugin developed based on the 3D Weka Segmentation plugin to allow semi-automatic detection of GFP+ CFs and to count and measure VGLUT2 clusters (https://github.com/orion-cirb/Vglut2_GFP_Weka_Maela.git). Gene clustering was performed using the open-source software Cluster 3.0 (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm).

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Acknowledgements

We would like to thank A. Boyreau for her help with some of the experimental procedures at the beginning of the project, Y. Dupraz for the development of tools for stereotaxic injections in neonates, F. Maloumian for her help with infographics and the personnel from the Center for Interdisciplinary Research in Biology animal and imaging facilities. We thank H. Monnet for her help in updating the plugin for VGLUT2 quantification. High-throughput qPCR was carried out on the qPCR-HD-Genomic Paris Centre platform, supported by grants from Région Ile-de-France. This work was supported by funding from Fondation pour la Recherche Médicale (Equipe FRM DEQ20150331748 to F.S.), European Research Council ERC consolidator grant (SynID 724601 to F.S.), Q-life (ANR-17-CONV-0005 to F.S. and V.H.), ANR-10-LABX-54 MEMO LIFE (to F.S.) and Sorbonne Université (ED158 to M.A.P.), Collège de France (to M.A.P.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Maëla A. Paul, Séverine M. Sigoillot.

Authors and Affiliations

  1. Center for Interdisciplinary Research in Biology (CIRB), Collège de France, Université PSL, CNRS, INSERM, Paris, France

    Maëla A. Paul, Séverine M. Sigoillot, Léa Marti, Francisco J. Urra Quiroz, Philippe Mailly & Fekrije Selimi

  2. Inovarion, Paris, France

    Francisco J. Urra Quiroz

  3. Plateforme qPCR-HD-GPC, Institut de Biologie de l’Ecole Normale Supérieure, Paris, France

    Marine Delagrange

  4. Department of Neuroscience, University of Connecticut Health, Farmington, CT, USA

    Hiu W. Cheung & David C. Martinelli

  5. The Connecticut Institute for the Brain and Cognitive Sciences (IBACS), Storrs, CT, USA

    David C. Martinelli

  6. Laboratoire de Physique de l’Ecole Normale Supérieure, CNRS, Ecole Normale Supérieure, PSL University, Sorbonne Université, Université de Paris, Paris, France

    Elie Oriol & Vincent Hakim

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  1. Maëla A. Paul
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Contributions

F.S., M.A.P. and S.M.S. conceptualized the project, developed the methodology and handled visualization. M.A.P., S.M.S., L.M., F.J.U.Q., M.D., P.M., H.W.C., E.O. and V.H. conducted the investigation. F.S. and M.A.P. secured funding. F.S. and S.M.S. provided supervision. F.S. managed project administration. F.S. wrote the original draft with contributions from S.M.S., M.A.P. and V.H. F.S., S.M.S., M.A.P., V.H. and D.C.M. reviewed and edited the final manuscript.

Corresponding author

Correspondence to Fekrije Selimi.

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Nature Neuroscience thanks Mary Hatten and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Developmental expression pattern of GC candidate genes in the cerebellar cortex.

a, The expression pattern of Cbln1 and the 15 selected GC candidate genes was assessed using high-throughput RT-qPCR on RNA extracts from the cerebellum taken at different stages of development (embryonic day, E17, postnatal days, P0, P3, P7, P14 and P21) and in adult mice. Expression levels were normalized to the Rpl13a gene and to their E17 value to capture their variation during postnatal development regardless of the individual gene’s expression level; data are presented as mean ± SEM. n = 4 animals per developmental stage and 3 animals for the adult. The data are separated into two graphs depending on the scale of dynamics of expression for clarity. b, Data from ref. 35 showing the stage of peak expression of the selected candidate genes depending on GC differentiation: GC precursors (GCPs) at P7, in newly differentiated GCs at P7, in migrating GCs at P12 and, finally, in mature GCs at P21. c, Single-cell expression data in cerebellar GCs from https://apps.kaessmannlab.org/sc-cerebellum-transcriptome/. Left: uniform manifold approximation and projection (UMAP) of mouse cerebellar cell types colored by cell differentiation state. GCP, granule cell precursor; UBCP, unipolar brush cell precursor; GC diff 1 and 2, differentiated GC1 and 2. Right: expression of Cbln1 and eleven GC DEGs candidates at different stages of GC differentiation. Dot size indicates the fraction of cells expressing a gene, color shows the mean expression level scaled by gene. d, smFISH of selected GC candidates (red) in cerebellar sections of P14 and adult mice co-stained with the nuclear stain DAPI. EGL, external granular layer; ML, molecular layer; IGL, internal granular layer. Each image corresponds to a projection of 15 images (z-stack step: 0.5 µm). Two independent experiments. Scale bars, 20 µm.

Source data

Extended Data Fig. 2 Developmental expression pattern of ION candidate genes in the inferior olive.

a, Expression patterns of C1ql1 and the 15 ION DEGs selected as candidates were assessed using high-throughput RT-qPCR on RNA extracts of the brainstem taken at different stages of development (embryonic day, E17, postnatal days, P0, P3, P7, P14 and P21) and in the adult. Expression levels were normalized to the Rpl13a gene and to their E17 value to capture their variation during postnatal development regardless of the individual gene’s expression level; data are presented as mean ± SEM. n = 4 animals per developmental stage and 3 animals for the adult. The data are separated into two graphs depending on the scale of dynamics of expression for clarity. b–d, Left: representative images from duplex smFISH experiments for C1ql1 and candidate mRNAs in coronal sections from the brainstem at P4, P14 and in adult mice. Scale bars, 150 µm. Right: the degree of correlation of expression between C1ql1 and candidate mRNAs in the brainstem was determined by computing the Pearson correlation coefficient on the whole image (coefficient >0.6 corresponding to high correlation91). Data are presented as mean ± SEM. b, Candidates highly correlated with C1ql1 at all developmental stages. Nrcam, n = 4 animals for each stage; Lgi2, adult: n = 5 animals, P14: n = 4, P4: n = 3; Crtac1, adult and P14: n = 4 animals, P4: n = 5; Sema4f, adult and P14: n = 3 animals, P4: n = 4; 2–4 independent experiments. c, Candidates highly correlated with C1ql1 from P14 to adult. Shisal1, n = 3 animals for each stage; Thy1, adult and P4: n = 3, P14: n = 4; Adam11, n = 3 for each stage; Crh: n = 3 for each stage; Gpr123, adult: n = 5 animals, P14 and P4: n = 4; 2–3 independent experiments. d, Candidates not highly correlated with C1ql1 at any stage. Tmem184b: n = 4 animals at each stage; Fstl1: n = 3 animals at each stage; Cx3cl1, adult and P14: n = 4 animals, P4: n = 3; Adam23: n = 4 animals at each stage; Cd151: n = 4 animals at each stage; Tmem179: n = 4 animals at each stage; 2–4 independent experiments.

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Extended Data Fig. 3 Predicted structure and localization of C1QL1, NRCAM, LGI2 and CRTAC1 in the cerebellar cortex.

a, AlphaFold structure prediction (left; database: https://alphafold.ebi.ac.uk/) and domain architecture (right) of C1QL1, NRCAM, LGI2 and CRTAC1. See also ref. 92 for the structure of the C1QL1 gC1q domain. Ig, immunoglobulin; FN, fibronectin; TMD, transmembrane domain; LRR, leucin reach repeat; EGF, epidermal growth factor; FG-GAP, phenylalanyl-glycyl-glycyl-alanyl-prolyl. b, Localization of C1QL1, NRCAM, LGI2 and CRTAC1 proteins (green) in the cerebellar cortex at P13 was obtained using several strategies: C1QL1, anti-HA immunolabeling in cerebellar sections from a C1ql1HA knockin mouse; NRCAM, anti-HA after CRISPR–Cas9-mediated HA-tagging of endogenous NRCAM; LGI2 and CRTAC1, immunolocalization after antigen retrieval. The CF presynaptic boutons and the dendritic trees of PCs were immunostained with anti-VGLUT2 (magenta) and anti-calbindin (CaBP, blue), respectively. Each image corresponds to a projection of 5 images (z-stack step: 0.2 µm). Arrowheads show candidates labeling colocalizing with VGLUT2 clusters. 3–4 independent experiments. Scale bars, 20 µm.

Extended Data Fig. 4 CRISPR–Cas9 knockdown for C1ql1, Nrcam, Lgi2 and Crtac1.

a, Top: illustrations of the genomic regions of mouse Nrcam, Lgi2, Crtac1 and C1ql1 with the location of the sequences targeted by the CRISPR–Cas9 gRNAs. Bottom: the knockdown efficiency for Nrcam, Lgi2 and Crtac1 was measured using quantitative RT-PCR on RNA extracts from cortical cell cultures from Cas9/GFP-KI mice (Nrcam, Lgi2 and Crtac1 are detected in these cultures at DIV14). The efficiency for C1ql1 was measured using mixed cerebellar cultures from Cas9/GFP-KI-NeuroD1Cre mice expressing the CAS9 specifically in GCs precursors (C1ql1 is transiently expressed in these cultures with a peak at DIV8). Cultures were transduced at 3 or 2 days in vitro (DIV3 or 2), respectively, with AAVs driving the expression of each gRNA directed against the candidate genes or non-targeting control gRNA (CTL). Expression levels were normalized to values for the Rpl13a gene. Data are presented as mean ± SEM. n represents the independent experiments: CTL, n = 5; Crtac1 KD g1, n = 3; Crtac1 KD g2, n = 4; Lgi2 KD g1, n = 7; Lgi2 KD g2, n = 3; Nrcam KD, n = 4; C1ql1 in all conditions, n = 4. Statistics: Kruskal–Wallis and uncorrected Dunn’s test. b, Duplex smFISH experiments for GFP and each candidate gene (C1ql1, Lgi2 and Crtac1), and nuclear DAPI staining, in coronal sections from the brainstem. Top: high magnification of IONs from P21 animals with C1ql1, Lgi2 or Crtac1 KD, or non-targeting controls (CTL). Scale bars, 10 µm. Bottom: relative frequency distribution and mean integrated intensity of each candidate gene mRNA per ION under KD and CTL conditions are shown. The dashed lines represent the first quartile and second quartile (median) of the mRNA levels for each gene in CTL condition. n > 55 cells, 7–8 animals per condition, 2–3 independent experiments. Insets: data are presented as violin plots with the median and quartiles. Statistics: two-tailed nested t test. c, Distribution and mean volume of the VGLUT2 clusters quantified in GFP+ CFs after Nrcam, Lgi2 or Crtac1 KD as well as in CTL. Data are presented as violin plots with the median and quartiles. n ≥ 33 images per condition, 9–10 animals; 3–5 independent experiments. Statistics: two-tailed nested t test.

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Extended Data Fig. 5 Cbln1 expression and function in IONs in the brainstem.

a, Heatmap showing the clustering of 324 DEGs according to the dynamics of their expression pattern in the brainstem between E17 and adult. Four clusters are highlighted by orange rectangles. Cbln1 is detected as an early-expressed gene. b, Top: illustration of the genomic region of mouse Cbln1 with the location of the sequence targeted by the CRISPR–Cas9 KD guide RNAs (Cbln1 KD g1 and g2) in Cbln1 exon 1 and exon 3, respectively. The location of forward (Fw) and reverse (Rev) primers used to assess deletion of the entire coding region is shown. Bottom left: efficiency of the CRISPR–Cas9 driven deletion was assessed by PCR on purified genomic DNA from DIV16 mixed cerebellar cultures (transduced at DIV2) or DIV14 neuronal cultures from the neocortex (transduced at DIV3). Wild-type fragment is expected at 2663 bp; recombined fragment at 380 bp. Right: duplex smFISH for GFP and Cbln1 mRNAs, and nuclear DAPI staining, in IONs from coronal brainstem sections of P7 mice expressing Cbln1 KD gRNAs or non-targeting CTL gRNA (GFP+). Scale bars, 10 µm. Relative frequency distribution and mean integrated intensity of Cbln1 mRNA per ION under KD and CTL conditions are shown. The dashed lines represent the first quartile and second quartile (median) of Cbln1 mRNA level in CTL condition. n ≥ 30 images per condition; 8–9 animals per condition, 2 independent experiments. Insets: data are presented as violin plots with the median and quartiles. Statistics: two-tailed nested t test. c, Distribution and mean volume of the VGLUT2 clusters were quantified in GFP+ CFs at P7 and P14 in CTL and Cbln1 KD. Data are presented as violin plots with the median and quartiles. P7 VGLUT2 cluster volume: n ≥ 29 images per condition; 8 animals, 4 independent experiments. P14 VGLUT2 cluster volume: n ≥ 33 images per condition; 8–9 animals, 3 independent experiments. Statistics: two-tailed nested t test.

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Extended Data Fig. 6 Modulation of neuronal excitability by Kir2.1 expression.

a, Neuronal cultures from the neocortex were transduced at DIV3 with a retrograde rAAV driving the expression of the Myc-tagged Kir2.1 (or nonfunctional Kir2.1 mutant as a control) and soluble eGFP under the CamKII promoter. Left: neurons were immunolabeled at DIV17 for Myc (blue) and GFP (green). Scale bars, 13 µm. Right: RNA extracts obtained from DIV14 cultures from neocortex were analyzed by quantitative RT-PCR. Gene expression levels relative to Rpl13a were normalized to the levels in Kir2.1 mutant control. Data are presented as mean ± SEM. Four independent experiments. Statistics: two-tailed Student’s t test with a null hypothesis of 1. b, In silico modeling of the effect of Kir2.1 channel expression on the activity of neurons from the inferior olive (IO). Left: representations of the discharge in neurons of the IO depending on the magnitude of the Kir2.1 conductance. Example of 10 s somatic voltage traces for different gKir conductances, ranging from gKir = 0 mS/cm2 to 0.5 mS/cm2, where, with a conservative unitary Kir2.1 channel conductance of 20 pS, 1 mS/cm2 corresponds to approximately 50 Kir2.1 channel per 100 μm2 of membrane. Right: mean firing rates and their standard deviations (for each value of gKir, n = 5 simulations of 100 s each). This modeling showed that a minimal level of Kir2.1 is needed for effective inhibition of ION activity. We selected a minimum threshold of approximately 40 Kir2.1 mRNA molecules per nucleus (as estimated by GFP mRNA intensity) to select IONs included for smFISH quantification.

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Extended Data Fig. 7 Localization of GluD2 and ADGRB3/BAI3 receptors in cerebellar Purkinje cells during postnatal development.

a,b, Immunostaining of GluD2 or ADGRB3/BAI3 receptors (green), CF presynaptic boutons (anti-VGLUT2, magenta) and PCs dendritic tree (anti-CaBP, blue) in parasagittal cerebellar sections from P4 and P13 mice. Left: low magnification images correspond to the projection of 5 planes (z-stack step: 0.2 µm). Scale bars, 20 µm. Right: airyscan images corresponding to single planes. Arrowheads show receptor labeling partially colocalizing with VGLUT2 clusters. Note that at P13, some GluD2 puncta are still detectable at CF/PC synapses. Three independent experiments. Scale bars, 4 µm.

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Paul, M.A., Sigoillot, S.M., Marti, L. et al. Stepwise molecular specification of excitatory synapse diversity onto cerebellar Purkinje cells. Nat Neurosci 28, 308–319 (2025). https://doi.org/10.1038/s41593-024-01826-w

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