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A trans-synaptic nanocolumn aligns neurotransmitter release to receptors

Nature volume 536, pages 210–214 (2016)Cite this article

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Abstract

Synaptic transmission is maintained by a delicate, sub-synaptic molecular architecture, and even mild alterations in synapse structure drive functional changes during experience-dependent plasticity and pathological disorders1,2. Key to this architecture is how the distribution of presynaptic vesicle fusion sites corresponds to the position of receptors in the postsynaptic density. However, while it has long been recognized that this spatial relationship modulates synaptic strength3, it has not been precisely described, owing in part to the limited resolution of light microscopy. Using localization microscopy, here we show that key proteins mediating vesicle priming and fusion are mutually co-enriched within nanometre-scale subregions of the presynaptic active zone. Through development of a new method to map vesicle fusion positions within single synapses in cultured rat hippocampal neurons, we find that action-potential-evoked fusion is guided by this protein gradient and occurs preferentially in confined areas with higher local density of Rab3-interacting molecule (RIM) within the active zones. These presynaptic RIM nanoclusters closely align with concentrated postsynaptic receptors and scaffolding proteins4,5,6, suggesting the existence of a trans-synaptic molecular ‘nanocolumn’. Thus, we propose that the nanoarchitecture of the active zone directs action-potential-evoked vesicle fusion to occur preferentially at sites directly opposing postsynaptic receptor–scaffold ensembles. Remarkably, NMDA receptor activation triggered distinct phases of plasticity in which postsynaptic reorganization was followed by trans-synaptic nanoscale realignment. This architecture suggests a simple organizational principle of central nervous system synapses to maintain and modulate synaptic efficiency.

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Figure 1: Vesicle release proteins form subsynaptic nanoclusters.
Figure 2: Release site mapping by pHuse in single synapses shows RIM predicts evoked fusion distribution.
Figure 3: Trans-synaptic nanoscale alignment of active zone and PSD proteins.
Figure 4: Retrograde plasticity of synaptic nanoscale alignment.

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References

  1. Fromer, M. et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. Volk, L., Chiu, S.-L., Sharma, K. & Huganir, R. L. Glutamate synapses in human cognitive disorders. Annu. Rev. Neurosci. 38, 127–149 (2015)

    Article  CAS  PubMed  Google Scholar 

  3. Franks, K. M., Stevens, C. F. & Sejnowski, T. J. Independent sources of quantal variability at single glutamatergic synapses. J. Neurosci. 23, 3186–3195 (2003)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. MacGillavry, H. D., Song, Y., Raghavachari, S. & Blanpied, T. A. Nanoscale scaffolding domains within the postsynaptic density concentrate synaptic AMPA receptors. Neuron 78, 615–622 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Nair, D. et al. Super-resolution imaging reveals that AMPA receptors inside synapses are dynamically organized in nanodomains regulated by PSD95. J. Neurosci. 33, 13204–13224 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Fukata, Y. et al. Local palmitoylation cycles define activity-regulated postsynaptic subdomains. J. Cell Biol. 202, 145–161 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Südhof, T. C. The presynaptic active zone. Neuron 75, 11–25 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Huang, B., Wang, W., Bates, M. & Zhuang, X. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  9. Dani, A., Huang, B., Bergan, J., Dulac, C. & Zhuang, X. Superresolution imaging of chemical synapses in the brain. Neuron 68, 843–856 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Park, H., Li, Y. & Tsien, R. W. Influence of synaptic vesicle position on release probability and exocytotic fusion mode. Science 335, 1362–1366 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Watanabe, S. et al. Ultrafast endocytosis at mouse hippocampal synapses. Nature 504, 242–247 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Balaji, J. & Ryan, T. A. Single-vesicle imaging reveals that synaptic vesicle exocytosis and endocytosis are coupled by a single stochastic mode. Proc. Natl Acad. Sci. USA 104, 20576–20581 (2007)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  13. Leitz, J. & Kavalali, E. T. Fast retrieval and autonomous regulation of single spontaneously recycling synaptic vesicles . eLife 3, e03658 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  14. Betzig, E. Single molecules, cells, and super-resolution optics (Nobel Lecture). Angew. Chem. Int. Ed. 54, 8034–8053 (2015)

    Article  CAS  Google Scholar 

  15. Levet, F. et al. SR-Tesseler: a method to segment and quantify localization-based super-resolution microscopy data. Nat. Methods 12, 1065–1071 (2015)

    Article  CAS  PubMed  Google Scholar 

  16. Raghavachari, S. & Lisman, J. E. Properties of quantal transmission at CA1 synapses. J. Neurophysiol. 92, 2456–2467 (2004)

    Article  CAS  PubMed  Google Scholar 

  17. Tarusawa, E. et al. Input-specific intrasynaptic arrangements of ionotropic glutamate receptors and their impact on postsynaptic responses. J. Neurosci. 29, 12896–12908 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dudek, S. M. & Bear, M. F. Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-d-aspartate receptor blockade. Proc. Natl Acad. Sci. USA 89, 4363–4367 (1992)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. Araki, Y., Zeng, M., Zhang, M. & Huganir, R. L. Rapid dispersion of SynGAP from synaptic spines triggers AMPA receptor insertion and spine enlargement during LTP. Neuron 85, 173–189 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lee, H.-K., Kameyama, K., Huganir, R. L. & Bear, M. F. NMDA induces long-term synaptic depression and dephosphorylation of the GluR1 subunit of AMPA receptors in hippocampus. Neuron 21, 1151–1162 (1998)

    Article  CAS  PubMed  Google Scholar 

  21. Sanderson, J. L. et al. AKAP150-anchored calcineurin regulates synaptic plasticity by limiting synaptic incorporation of Ca2+-permeable AMPA receptors. J. Neurosci. 32, 15036–15052 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Davis, G. W. & Müller, M. Homeostatic control of presynaptic neurotransmitter release. Annu. Rev. Physiol. 77, 251–270 (2015)

    Article  CAS  PubMed  Google Scholar 

  23. Liu, K. S. et al. RIM-binding protein, a central part of the active zone, is essential for neurotransmitter release. Science 334, 1565–1569 (2011)

    Article  ADS  CAS  PubMed  Google Scholar 

  24. Holderith, N. et al. Release probability of hippocampal glutamatergic terminals scales with the size of the active zone. Nat. Neurosci. 15, 988–997 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nakamura, Y. et al. Nanoscale distribution of presynaptic Ca2+ channels and its impact on vesicular release during development. Neuron 85, 145–158 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Scimemi, A. & Diamond, J. S. The number and organization of Ca2+ channels in the active zone shapes neurotransmitter release from Schaffer collateral synapses. J. Neurosci. 32, 18157–18176 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Schneider, R. et al. Mobility of calcium channels in the presynaptic membrane. Neuron 86, 672–679 (2015)

    Article  CAS  PubMed  Google Scholar 

  28. Tarr, T. B., Dittrich, M. & Meriney, S. D. Are unreliable release mechanisms conserved from NMJ to CNS? Trends Neurosci. 36, 14–22 (2013)

    Article  CAS  PubMed  Google Scholar 

  29. Lisman, J. & Raghavachari, S. A unified model of the presynaptic and postsynaptic changes during LTP at CA1 synapses. Sci. STKE 2006, re11 (2006)

  30. Missler, M., Südhof, T. C. & Biederer, T. Synaptic cell adhesion. Cold Spring Harb. Perspect. Biol . 4, a005694 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Frost, N. A., Shroff, H., Kong, H., Betzig, E. & Blanpied, T. A. Single-molecule discrimination of discrete perisynaptic and distributed sites of actin filament assembly within dendritic spines. Neuron 67, 86–99 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kaech, S. & Banker, G. Culturing hippocampal neurons. Nat. Protocols 1, 2406–2415 (2006)

    Article  CAS  PubMed  Google Scholar 

  33. van de Linde, S. et al. Direct stochastic optical reconstruction microscopy with standard fluorescent probes. Nat. Protocols 6, 991–1009 (2011)

    Article  CAS  PubMed  Google Scholar 

  34. Schneider Gasser, E. M. et al. Immunofluorescence in brain sections: simultaneous detection of presynaptic and postsynaptic proteins in identified neurons. Nat. Protocols 1, 1887–1897 (2006)

    Article  CAS  PubMed  Google Scholar 

  35. Geisler, C. et al. Drift estimation for single marker switching based imaging schemes. Opt. Express 20, 7274–7289 (2012)

    Article  ADS  PubMed  Google Scholar 

  36. Mlodzianoski, M. J. et al. Sample drift correction in 3D fluorescence photoactivation localization microscopy. Opt. Express 19, 15009–15019 (2011)

    Article  ADS  PubMed  Google Scholar 

  37. Thompson, R. E., Larson, D. R. & Webb, W. W. Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82, 2775–2783 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Schikorski, T. & Stevens, C. F. Quantitative ultrastructural analysis of hippocampal excitatory synapses. J. Neurosci. 17, 5858–5867 (1997)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Veatch, S. L. et al. Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting. PLoS One 7, e31457 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kim, S. H. & Ryan, T. A. CDK5 serves as a major control point in neurotransmitter release. Neuron 67, 797–809 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Voglmaier, S. M. et al. Distinct endocytic pathways control the rate and extent of synaptic vesicle protein recycling. Neuron 51, 71–84 (2006)

    Article  CAS  PubMed  Google Scholar 

  42. Harris, K. M. & Stevens, J. K. Dendritic spines of CA 1 pyramidal cells in the rat hippocampus: serial electron microscopy with reference to their biophysical characteristics. J. Neurosci. 9, 2982–2997 (1989)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Simonson, P. D., Rothenberg, E. & Selvin, P. R. Single-molecule-based super-resolution images in the presence of multiple fluorophores. Nano Lett. 11, 5090–5096 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  44. Thompson, M. A., Lew, M. D. & Moerner, W. E. Extending microscopic resolution with single-molecule imaging and active control. Annu. Rev. Biophys. 41, 321–342 (2012)

    Article  CAS  PubMed  Google Scholar 

  45. Chen, T.-W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Murthy, V. N., Sejnowski, T. J. & Stevens, C. F. Dynamics of dendritic calcium transients evoked by quantal release at excitatory hippocampal synapses . Proc. Natl Acad. Sci. USA 97, 901–906 (2000)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  47. Xie, X., Liaw, J.-S., Baudry, M. & Berger, T. W. Novel expression mechanism for synaptic potentiation: alignment of presynaptic release site and postsynaptic receptor. Proc. Natl Acad. Sci. USA 94, 6983–6988 (1997)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kavalali, E. T. et al. Spontaneous neurotransmission: an independent pathway for neuronal signaling? Physiology (Bethesda) 26, 45–53 (2011)

    CAS  Google Scholar 

  49. Frank, T. et al. Bassoon and the synaptic ribbon organize Ca2+ channels and vesicles to add release sites and promote refilling. Neuron 68, 724–738 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Ermolyuk, Y. S. et al. Differential triggering of spontaneous glutamate release by P/Q-, N- and R-type Ca2+ channels. Nat. Neurosci. 16, 1754–1763 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank S. Thompson, T. Abrams, S. Jurado and G. Wittenberg for advice and comments, P. Kaeser for advice on RIM expression and RIM antibodies, Y. Araki and R. Huganir for advice on chemLTP, and S. S. Divakaruni for advice and initial tests of chemLTP. We thank P. Kaeser for the gift of RIM1-mVenus, T. Ryan for vGlut1-pHluorin-mCherry, G. Augustine for Syn1a–CFP, and M. Contreras for technical assistance. This work was supported by F30-MH105111 to H.C., F30-MH102891 to T.P.L., F31-MH105105 to S.R.M., T32-GM008181 to H.C. and S.R.M., R01-MH080046 and NS090644 to T.A.B, and a gift from the Kahlert Foundation to T.A.B.

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Author notes

  1. Ai-Hui Tang and Haiwen Chen: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Physiology, University of Maryland School of Medicine, Baltimore, 21201, Maryland, USA

    Ai-Hui Tang, Haiwen Chen, Tuo P. Li, Sarah R. Metzbower & Thomas A. Blanpied

  2. Program in Neuroscience, University of Maryland School of Medicine, Baltimore, 21201, Maryland, USA

    Ai-Hui Tang, Haiwen Chen, Tuo P. Li, Sarah R. Metzbower & Thomas A. Blanpied

  3. Medical Scientist Training Program, University of Maryland School of Medicine, Baltimore, 21201, Maryland, USA

    Haiwen Chen & Tuo P. Li

  4. Department of Biology, Cell Biology, Faculty of Science, Utrecht University, Utrecht, 3584 CH, The Netherlands

    Harold D. MacGillavry

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Contributions

A.T. and H.C. performed STORM experiments, A.T. designed 3D-STORM analysis, H.C. performed and analysed pHuse and RIM PALM experiments, T.P.L. and A.T. performed simulations, S.R.M. performed GCaMP imaging and nanobody STORM experiments, H.D.M. performed PSD PALM experiments, and A.T., H.C. and T.A.B. designed the experiments and wrote the manuscript.

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Correspondence to Ai-Hui Tang or Thomas A. Blanpied.

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The authors declare no competing financial interests.

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Nature thanks S. Sigrist, X. Zhuang and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Filtering of localizations and automatic algorithm to detect the synaptic axis.

a, Scatter plot of fitted peak width in y (Wy) against that in x (Wx). The colour codes the position in z. All localizations away from this centre dense region arise from multiple overlapping or poorly fitted peaks and should be rejected. b, The ellipticity (Wx/Wy) and the width difference (Wx − Wy) formed an approximate linear relationship when Wx > Wy (dotted box). c, We fitted the ratios between ellipticity and the width difference to the denominators with third degree polynomial functions (black line) and rejected all localizations out of 95% confidence intervals (grey lines) of the curve (>1.96 × s.d.). The same criteria was applied to the other fraction of localizations with Wx < Wy. d, The same scatter plot as in a after rejection of all of the diffuse localizations (about 20–25%). e, f, The filtering protocol cleared up most of the localizations from multiple overlapping peaks or poorly fitted peaks, including most of the non-relevant background localizations (e) and those localizations with poorly calibrated z positions (f). Scale bars, 2 μm (e) and 200 nm (f). The synapse in f corresponds to the boxed synapse in e. g, A 2D section through the centre of the convoluted constructed 3D distribution matrix of a synapse. h, Peak density of the matrix set to a quarter of the mean molecule density of the synaptic cluster. i, 2D section at the same position of the 3D matrix of direct cross-correlation of the two channels (equation (3) in Methods). C is the centre of matrix, and A is the peak of the cross-correlation. j–k, Best overlap of the two synaptic clusters after PSD-95 was moved in 3D space along the vector . l, 3D scatter plots of the synapse in two different view angles. The arrow denotes the vector and the extended line (dotted) represents the synaptic axis. m, 3D plot of detected synaptic axis when the positions of high-density peaks in RIM1/2 (nanoclusters) were randomized within the synaptic cluster. This simulation was performed 35 times, but only 10 representative results are presented here to avoid overlapping. The red denotes the synaptic axis of the original synaptic cluster. n, Averaged distance between the detected Cn positions from 35 simulated clusters to the C position of the original cluster. Data shown in mean ± s.d. This <6 nm distance confirms that the high-density peaks have negligible effect on the detection of the synaptic axis in this Method. o, Distribution of all localizations along the synaptic axis with bin size of 10 nm. Peak-to-peak distance between the synaptic protein pair can be measured from this distribution. p–r, Distribution of peak-to-peak distances for three pairs of synaptic proteins.

Extended Data Figure 2 Nanocluster organization of vesicle release machinery proteins in the active zone and postsynaptic AMPA receptors.

a, En face (top) and side (bottom) views of local density maps of a simulated synapse with artificial nanoclusters with 40-nm diameters. Scale bar, 100 nm. b, Autocorrelation function of simulated clusters with different sized nanoclusters. The points represent the radius where g(r) = 1. c, Pooled data from 15 sets of simulations showing that the radius where g(r) first crosses 1 reasonably estimates the average nanocluster diameters. d, Comparison of nanocluster number, fraction of localization in nanocluster, and nanocluster volume across different developmental stages shows no significant difference, though the young 9 days in vitro (DIV) culture shows a trend towards increased nanocluster numbers (one-way ANOVA on ranks for nanocluster number and volume, one-way ANOVA for percentage localization in nanocluster). Data were from 143 RIM nanoclusters and 135 PSD nanoclusters of 64 DIV 9 synapses, 63 RIM nanoclusters and 65 PSD nanoclusters of 38 DIV 14 synapses, and 44 RIM nanoclusters and 41 PSD nanoclusters from 28 DIV 21 synapses. e, Comparison of two RIM antibodies (from left to right) in whole synaptic cluster volume, number of nanoclusters, autocorrelation function estimating average nanocluster diameter, and protein density relative to PSD-95 nanocluster centres. Anti-RIM1/2 (Synaptic Systems #140-203) targets the zinc-finger domain and anti-RIM1 targets the PDZ domain of RIM1 (Synaptic Systems #140-003). These tests suggest that there is no significant difference between these two antibodies. The numbers in bars denote the group sizes. f, Local density maps of en face (top) and side (bottom) views of an example Munc13 cluster. Scale bar, 200 nm. g, Auto-correlation functions for Munc13 distributions compared to simulated randomized distributions. h, i, Local density maps and ACF of Bsn cluster. Scale bar, 200 nm. j, Pooled cluster volumes, normalized to PSD-95 volumes within each synapse. Each bar pair represents data from a set of RIM1/2-PSD-95, Munc13-PSD-95 or Bsn-PSD-95 staining. The numbers in bars denote the group sizes. k, Distribution of en face distances between nanocluster centre and synapse centre. Data were normalized to the distribution of simulated clusters with the same number of nanoclusters as the original synapse but randomized positions. l, An example synapse with RIM1/2 and Munc13 staining of the same synapse, shown in two different angles. The translucent surfaces represent the alpha shapes that define the synaptic cluster borders. m, Pooled RIM1/2 and Munc13 cluster volumes, normalized to RIM1/2 within each synapse. n, Pooled RIM1/2, Munc13 and Bsn cluster volumes from staining of RIM1/2-Bsn and Munc13-Bsn, normalized to Bsn within each synapse. *P < 0.05; ***P < 0.001; Wilcoxon signed-rank test. †P < 0.05, one-way ANOVA on ranks with pairwise comparison procedures (Dunn’s method). o, Local density map of a GluA2 cluster. p, Auto-correlation functions for GluA2 distributions compared to simulated randomized distributions. q, Local density map of a GluR2/3 cluster. r, Auto-correlation functions for GluR2/3 distributions compared to simulated randomized distributions. All experiments were repeated ≥3 times.

Extended Data Figure 3 Detected nanoclusters are unlikely a result of labelling artefacts or overcounting of molecules.

a–i, Comparison of PSD-95 labelled with monoclonal primary antibodies directly conjugated to Alexa647 dye (1°-A647, red) with the same molecules labelled with primary and secondary antibodies conjugated to Cy3 (1°-2°-Cy3, blue) as represented in c. a, b, Comparison between non-synaptic small groups of localizations arising from isolated primary antibodies and secondary antibodies. Schematic shown in a. Standard deviation of localizations in both groups along different dimensions (n = 32 for A647; n = 36 for Cy3) in b. The two types of localizations groups showed similar variation in all dimensions. d, Local density maps of the same PSD-95 cluster labelled with 1°-A647 (top) and 1°-2°-Cy3 (middle) and overlapped distribution of 1°-A647 and 2°-Cy3 with detected nanoclusters highlighted in darker colours (bottom). Scale bar, 200 nm. e, Autocorrelation of synaptic clusters labelled with 1°-A647 and 1°-2°-Cy3. f, Autocorrelation of isolated small groups of localizations of A647 and Cy3 dyes. g, Comparison of the radius at which the autocorrelation function crossed with the random level (g(r) = 1). There was no difference between PSD-95 clusters with different labelling methods, but the r(0) for isolated localization groups were significantly less than r(0) for PSD-95 clusters. **P < 0.01, t-test between the filled and open bars of the same colour. h, Nanoclusters detected in both channels displayed no difference in number, volume, or the fraction of nanoclusters enriched with localizations from the other channel. i, Protein enrichment of localizations detected in each channels with those in the other channel (n = 32 synapses). These results demonstrate that the nanoclusters we detected in our study were not due to aggregation of multiple secondary antibodies to the primary antibodies. j–r, Cells transfected with knockdown-rescue-PSD-95-GFP were labelled with nanobodies against GFP conjugated at a 1:1 ratio with Atto647 (Nb-At647, red) and primary/secondary antibodies against PSD-95 (1°-2°-Cy3, blue) as depicted in l. j, k, Comparison between non-synaptic small groups of localizations arising from isolated Nb-At647 and 1°-2°-Cy3 (as depicted in j, n = 26 and 28, respectively). k, The nanobodies showed a significant smaller size than antibodies. ***P < 0.001, two-way ANOVA, †P < 0.05, ††P < 0.01, pairwise comparison (Tukey test) between nanobodies and antibodies. m–r, Similar comparison as in d–i between PSD-95 clusters labelled with Nb-At647 and 1°-2°-Cy3 (n = 13 synapses). Scale bar, 200 nm. Overall, these results demonstrated that the nanoclusters we detected in our study were unlikely a result of artefacts of antibody binding and labelling. The difference between the size of the isolated localizations groups and PSD-95 clusters calculated by autocorrelation also argues against the possibility that the nanoclusters we detected were owing to repetitive switching of one or a few fluorophores. **P < 0.01, t-test between the filled and open bars of the same colour. s, An example synapse with nanoclusters highlighted before (upper) and after (lower) removal of localizations resulting from fluorophores lasting for multiple frames. Scale bar, 100 nm. t, Paired autocorrelation function of synaptic clusters with and without multiple-frame molecules. P = 0.77, n = 25 synapses for RIM1/2; P = 0.58, n = 25 synapses for PSD-95, two-way ANOVA with repeated measures. u, The tracking removed 13 ± 8% and 17 ± 9% of the localizations for RIM1/2 and PSD-95, respectively, but had no significant effects on autocorrelation function results, nanocluster numbers, or nanocluster volumes. **P < 0.01; ***P < 0.001; NS, P > 0.05; Wilcoxon signed-rank test. All data were pooled from ≥3 replicas.

Extended Data Figure 4 1AP evoked release is [Ca2+] dependent and mainly univesicular48.

a, Example of fluorescence signals at a single bouton over repeated trials of 1 action potential stimulation. b, Single event traces of vGpH fluorescence increase following 1 action potential stimuli in standard (2 mM) or heightened extracellular [Ca2+] (4 mM). c, Comparison of distributions of fluorescence changes in 2 mM (n = 233/27) and 4 mM (n = 115/12) extracellular [Ca2+], relative to noise distributions obtained from the baseline frames before stimulation. d, Comparison of noise-subtracted distributions of fluorescence changes in different [Ca2+]. e, Processed images of vGpH fluorescence increase following 1 action potential stimuli from three trials ten trials apart. f, Automatic detection using pHuse of events shown in e. g, Summed projection of framewise and background subtracted vGpH fluorescence increases over 60 trials. h, pHuse localizations on Syn1a (white). i–l, Same as e–h for spontaneous events in TTX over 5 min. n given in synapses/experiments.

Extended Data Figure 5 pHuse reveals differences between evoked and spontaneous fusion site areas.

a, Comparison of spontaneous frequency measured presynaptically using vGpH (n = 77/22) and postsynaptically using GCaMP6f (ref. 45) (n = 61/5), t = 1.02, not significant. b, Average bouton areas across groups, t = 0.87, not significant. c, Cumulative distributions of fusion areas for spontaneous and evoked release (Kolmogorov–Smirnov test, *D = 0.23) d, Cumulative distributions of normalized fusion areas for 1 AP evoked fusion excluding events with photon counts > mean + 2 s.d. of spontaneous events (n = 91/27) compared to all evoked events (n = 104/28, Kolmogorov–Smirnov test, D = 0.05, not significant) and spontaneous events (n = 77/22, Kolmogorov–Smirnov test, *D = 0.25) e, f, Notably, while evoked Pr was significantly positively correlated with Syn1a area, as reported previously49, spontaneous event frequency showed no relationship with Syn1a area (e, linear fit, evoked **R = 0.30, spontaneous R = 0.12, not significant). On the other hand, both spontaneous event frequency and evoked Pr significantly positively correlated with pHuse area (f, linear fit, evoked ***R = 0.64, spontaneous ***R = 0.60). This suggests that pHuse area may be a better approximation for active zone area and the functional parameters of a synapse than bouton area. g, Normalized pHuse area as a function of cell age shows no significant correlation (evoked R = 0.03, not significant, spontaneous R = 0.004, not significant). e–g, nevoked = 104/28, nspont = 77/22. h. Normalized pHuse area was not significantly different at room temperature (nevoked = 51/10, nspont = 32/7) versus physiological temperature (nevoked = 35/9, nspont = 34/4) within modes of release but still significantly different between modes of release. i, Normalized pHuse area was not significantly different at different thresholds for Syn1a within modes of release but still significantly different between modes of release (n = 51/10). j, Both numbers of events and mode of release are significant factors for pHuse area, but they do not have a significant interaction nevoked = 155/38, nspont = 109/29. For i, j, see Supplementary Tables for statistics. n given in synapses/experiments, *P < 0.05; **P < 0.01; ***P < 0.001.

Extended Data Figure 6 RIM1-mEos3.1 PALM identifies nanoclusters.

a, Neurons co-expressing RIM1-mVenus (a gift from P. Kaesar) and Syn1a–CFP colocalize to the same boutons. Right panels show enlargement of areas within the white boxes. Scale bars, 5 μm (left) and 1 μm (right). b. Neurons expressing RIM1-mVenus immunostained for RIM1/2 and Bsn. Arrowheads point to some colocalized active zones. Scale bar, 2 μm. c, Immunofluorescence intensity of transfected cells normalized to nearby untransfected cells show 3.74 ± 0.11-fold overexpression of RIM and 1.24 ± 0.03-fold increase in Bsn (n = 262 synapses/7 cells). d, Photon count distribution of RIM1-mEos3.1 (3997 localizations). e, Same boutons shown in Fig. 2 visualized using 5 × nearest neighbour density (NND) as a measure of local density. f–h, Cumulative distributions of PALMed RIM1 nanoclusters diameter, area, and number, respectfully, identified using adapted Tesseler analysis and 5 × NND analysis (n = 65/13). i, RIM1 localization density as a function of radial distance from pHuse localizations. (See Supplementary Tables for statistics.) j, Mean distance from pHuse localizations as a function of local density measured by 5 × NND (raw data ***R = 0.23, n = 26/13). k, Proportion of pHuse localizations within 40 nm of a RIM1 localization as a function of RIM1 local density measured by 5 × NND (***R = 0.35). n given in synapses/experiments unless otherwise specified, ***P < 0.001.

Extended Data Figure 7 Protein enrichment within nanocolumns.

a, Enrichment index between RIM1/2 and PSD-95. The left insets are replicas of Fig. 3e, and the enrichment index is defined as the average of the first three bins in the enrichment profile (boxed), that is, normalized localization density within 60 nm from the projection centre of a given nanocluster. Filled points show RIM1/2 relative to PSD-95 nanoclusters, open points show PSD-95 relative to RIM1/2 nanoclusters. Same randomizations as in Fig. 3e and depicted again in b. **P < 0.01; ***P < 0.001, one-way ANOVA on ranks with pairwise comparison procedures (Dunn’s method). b, The fraction of enriched nanoclusters is significantly above chance level, and is also dependent on the relative position of the two sets of nanoclusters. c, d, Side and en face views of a synaptic Munc13 and PSD-95 pair and a synaptic Bsn and PSD-95 pair with highlighted nanoclusters. Scale bar, 200 nm. e, Pooled enrichment index of three active zone proteins and PSD-95. Scale bar, 200 nm. Filled points show active zone proteins relative to PSD-95 nanoclusters, open points show PSD-95 relative to active zone protein nanoclusters. **P < 0.01; ***P < 0.001, one-way ANOVA on ranks with pairwise comparison procedures (Dunn’s method). f, Example of RIM1/2 and PSD-95 in adult hippocampal slices. g, Auto-correlation functions of RIM1/2 and PSD-95 (n = 192 and 43 synapses, respectively). There were, on average, 2.02 ± 0.08 and 1.32 ± 0.21 nanoclusters with a volume of (3.6 ± 0.2) and (4.2 ± 0.7) × 105 nm3 for RIM1/2 and PSD-95, respectively. Except PSD nanocluster number which was significantly less than that in cultures (P = 0.03), all other parameters were similar (Wilcoxon signed-rank test). h, Enrichment profile between RIM1/2 and PSD-95 in tissue slices (28 synapses from 7 sections, 4 animals). *P < 0.05 between measured and randomized synapses, two way ANOVA with pairwise comparison procedures (Dunn’s method).

Extended Data Figure 8 Preferential release in nanocolumns can increase synaptic strength.

a, Schematic of the experimentally constrained, deterministic approach used to study the dependence of synaptic strength on the spatial distribution of release sites and AMPARs. The simulated release site distribution at a synapse was drawn from its measured RIM positions and the average measured relationship between RIM density and pHuse locations (Fig. 2). b, Distributions of measured RIM localizations within a single active zone (active zone) boundary (grey), and the same cluster with randomized positions of the indicated subsets of molecules. c, Maps of RIM local density normalized to the overall densities within the active zones. d, Probability density maps of possible release sites given that a release occurs. e, Distributions of GluA2/3 locations within the PSD boundary (grey) of the same measured synapse (ellipses refer to this distribution) and randomized. f, Maps of fraction of open channels at peak response per average release from the respective active zones directly above them in d. g, Calculated open channels at peak response, n = 20 randomly generated molecular distributions. See Methods for more details.

Extended Data Figure 9 Enrichment of other scaffolding proteins within nanocolumns.

a, Enrichment of Homer1 with PSD-95 nanoclusters, n = 118 nanoclusters from 48 synapses, scale 100 nm. b, Enrichment of RIM1/2 to Shank nanoclusters, n = 80 nanoclusters from 32 synapses. Scale bar, 200 nm. *P < 0.05, ANOVA on ranks with pairwise comparison procedures (Dunn’s method) in a and b. c, GKAP2 and Shank3 densities (determined with STORM, n = 6 and 12, respectively) within PSD-95 nanoclusters (determined with PALM of transfected knockdown-replacement-PSD-95-mEos2) normalized to total PSD densities. Both proteins showed significant enrichment in PSD-95 nanoclusters, *P < 0.05, paired t-tests. d, Three-colour STORM imaging of RIM1/2, GKAP1 and PSD-95 on the same synapses example (left) and protein enrichment profiles of RIM1/2 and GKAP1 with respect to PSD-95 nanoclusters (right), n = 32 nanoclusters from 17 synapses. Scale bar, 200 nm. e, Enrichment indices of RIM1/2 and GKAP1 relative to PSD-95 nanoclusters. Colour-coded bars represent the same set of randomizations as performed in Fig. 3c: orange denotes randomization of only out-of-nanocluster localizations, cyan denotes randomization of nanocluster positions within synaptic clusters and grey denotes randomization of all localizations. f, The percentage of PSD-95 nanoclusters that were enriched with GKAP1, RIM1/2 or both with colour-coded randomizations. *P < 0.05; **P < 0.01, ANOVA on ranks with pairwise comparison procedures (Dunn’s method), n = 32 nanoclusters from 17 synapses in 7 different cultures. g, Schematic summary of the distribution of synaptic proteins within nanocolumns. The distributions of colour-coded proteins are based on our results and the proteins in grey are hypothetical, some, such as Ca2+ channels, have been suggested previously to be clustered49,50. All experiments were repeated ≥5 times.

Extended Data Figure 10 Plasticity within nanocolumns.

a, Changes in the localization density within RIM1/2 (red) and PSD-95 (blue) nanoclusters under control, 5 min NMDA treatment, 25 min washout, and NMDA + AP5 treatment conditions. b–h, Reorganization of RIM1/2 and GluR2/3 under control, 5 min NMDA treatment, 25 min washout conditions examples (b), comparison of whole synaptic cluster sizes (c), nanocluster number per synapse (d), localization density within nanoclusters (e), enrichment indices (f), percentage of nanoclusters that were enriched (g), and nanocluster volumes (h). Note that similar to the results from the RIM1/2-PSD-95 analyses, only those RIM1/2 nanoclusters that were enriched with GluR2/3 (dark red) were increased in volume. *P < 0.05; **P < 0.01, ANOVA on ranks with pairwise comparison to control group (Dunn’s method), and χ2 test for the proportion. Data from 62, 21 and 37 nanoclusters from 34, 18 and 24 synapses for control, NMDA, and washout, respectively. i, Colour-coded local density map of an example live-PALMed PSD-95 cluster before and after NMDA treatment. Scale bar, 100 nm. j, k, Changes in PSD-95 nanocluster area induced by NMDA and blocked by AP5 (n = 28 and 21, respectively). **P < 0.01, NS, not significant, paired t-test. l–n, LTP stimulation induced changes in nanocluster volumes (l), localization density within nanoclusters (m) and nanocluster numbers (n). *P < 0.05, ANOVA on ranks with pairwise comparison to control group (Dunn’s method). All experiments were repeated ≥5 times.

Supplementary information

Supplementary Information

This file contains links to further information about the antibodies used and Supplementary Tables 1-3. (PDF 132 kb)

3D rotation of RIM1/2 and PSD-95 molecules from a synapse

Each dot represents one localization obtained from STORM imaging. Red represents RIM1/2 and blue is PSD-95. The left side shows the local density, with thicker colour denoting higher density. The right side shows identified nanoclusters in thick colour. (MOV 18683 kb)

Animated model of transsynaptic alignment

Measured localizations of RIM1/2 and PSD-95 at one synapse are taken as the starting point for illustrating nanocolumn organization in context. The model is to scale, and protein features are derived from crystal structures where possible. Cell structure and the position of vesicles and other molecules are hypothetical. Columnar guides indicate where the peaks of protein gradients align across the cleft, as deduced using methods from the paper. (Animation created by Jim Stanis http://www.jimstanis.com.) (MOV 26246 kb)

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Tang, AH., Chen, H., Li, T. et al. A trans-synaptic nanocolumn aligns neurotransmitter release to receptors. Nature 536, 210–214 (2016). https://doi.org/10.1038/nature19058

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