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Synaptic weight set by Munc13-1 supramolecular assemblies

Nature Neuroscience volume 21, pages 41–49 (2018)Cite this article

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Abstract

The weight of synaptic connections, which is controlled not only postsynaptically but also presynaptically, is a key determinant in neuronal network dynamics. The mechanisms controlling synaptic weight, especially on the presynaptic side, remain elusive. Using single-synapse imaging of the neurotransmitter glutamate combined with super-resolution imaging of presynaptic proteins, we identify a presynaptic mechanism for setting weight in central glutamatergic synapses. In the presynaptic terminal, Munc13-1 molecules form multiple and discrete supramolecular self-assemblies that serve as independent vesicular release sites by recruiting syntaxin-1, a soluble N-ethylmaleimide-sensitive-factor attachment receptor (SNARE) protein essential for synaptic vesicle exocytosis. The multiplicity of these Munc13-1 assemblies affords multiple stable states conferring presynaptic weight, potentially encoding several bits of information at individual synapses. Supramolecular assembling enables a stable synaptic weight, which confers robustness of synaptic computation on neuronal circuits and may be a general mechanism by which biological processes operate despite the presence of molecular noise.

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Fig. 1: Imaging of glutamate release at single synapses.
Fig. 2: Multiple quantal release sites at single synapses.
Fig. 3: Munc13-1 determines the number of quantal release sites at individual synapses.
Fig. 4: Munc13-1 nanoassembly corresponds to the quantal release site.
Fig. 5: Munc13-1 assembles with syntaxin-1 at the AZ.
Fig. 6: Reconstitution of release site supramolecular assemblies in non-neuronal cells.
Fig. 7: Supramolecular assembling model for synaptic vesicle release site.

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Acknowledgements

We thank S. Iinuma for development of the glutamate sensor in preliminary experiments, A. Onuma and Y. Osakaya for technical assistance, N. Brose (Max Planck Institute) for providing the Munc13-1-EGFP construct, S. Kozaki (Osaka Prefecture University) for providing the BoNT/C-HC construct, and T. Kohda (Osaka Prefecture University) for preliminary preparation of the BoNT/C-HC protein. We also thank M. Iino for comments on the manuscript. This work was supported by the “Development of biomarker candidates for social behavior” study carried out under the Strategic Research Program for Brain Sciences by the Ministry of Education, Culture, Sports, Science and Technology of Japan (to K.H.), KAKENHI (grant nos. 24116004 and 17H04029 to K.H., 24590313, 25115704, 15K15048 and 24115502 to S.N. and 16H01416 to D.A), SENTAN, JST (to K.H.) and The Tokyo Society of Medical Sciences (to S.N.).

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  1. Department of Neurobiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Hirokazu Sakamoto, Tetsuroh Ariyoshi, Naoya Kimpara, Kohtaroh Sugao, Isamu Taiko, Kenji Takikawa, Daisuke Asanuma, Shigeyuki Namiki & Kenzo Hirose

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Contributions

H.S., S.N. and K.H. conceived and designed the study. H.S. performed most of the experiments, analyzed the data and wrote a draft of the manuscript. T.A. performed reconstitution experiments. S.N. and N.K. prepared biological specimens. K.S. and I.T. prepared shRNA constructs. K.T. and D.A. prepared the eEOS. K.H. supervised the collection of data and revised the draft. All authors discussed the results and commented on the manuscript.

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Correspondence to Kenzo Hirose.

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Integrated Supplementary Information

Supplementary Figure 1 Counting the number of releasable vesicles at single synapses by deconvolution analysis of glutamate imaging.

a Time courses of fluorescence responses of eEOS at five single synapses evoked by 20 stimuli at 50 Hz with 4 mM [Ca2+]e in the presence of 20 µM 4-AP are shown. Grey traces show individual trials, and the black bold traces show the averaged responses of five trials. The signal amplitude of fluorescence responses of eEOS was highly variable among synapses. Orange bars represent the timing of stimuli. b Vesicular release rate derived from averaged fluorescence responses of eEOS by deconvolution analysis. c Cumulative vesicular release. The linear fits (red dashed trace) of slow components of release superimposed on the cumulative vesicular release provide the estimation of N RRV . The N RRV largely varied from synapse to synapse.

Supplementary Figure 2 Evaluating the validity of multiple-probability fluctuation analysis of glutamate imaging.

a Histogram analysis of fluorescence responses of eEOS at a single synapse under conditions of multiple release probabilities (related to Fig. 2c,d). The color coding is the same as in Fig. 2c: blue, 0.5 mM (n = 100 events); cyan, 1 mM (n = 100 events); green, 1.5 mM (n = 50 events); white, 2 mM (n = 50 events); orange, 4 mM (n = 50 events); red, 4 mM [Ca2+]e plus 4-AP (n = 50 events). Dashed lines show binomial release model distributions generated with quantal parameters estimated by multiple-probability fluctuation analysis in Fig. 2d. N site  = 3, Q = 3.1 %, P = 0.01, 0.04, 0.14, 0.23, 0.51, and 0.83, respectively, Background noise standard deviation (SD) of 0.5 % and quantal variability (CV = 0.28) were also taken into account for the distribution. Cramér–von Mises test was used for testing goodness-of-fit. P = 0.94 (T = 0.039) for 0.5 mM [Ca2+]e, P = 0.073 (T = 0.40) for 1 mM [Ca2+]e, P = 0.46 (T = 0.13) for 1.5 mM [Ca2+]e, P = 0.83 (T = 0.058) for 2 mM [Ca2+]e, P = 0.92 (T = 0.043) for 4 mM [Ca2+]e, and P = 0.59 (T = 0.098) for 4 mM [Ca2+]e plus 4-AP. Panels beneath the histograms depict corresponding averaged glutamate signal images, and arrows indicate the analyzed synapse. b Relationship between expected and observed success rates of glutamate release at the same synapse in a, showing very good agreement between them. The expected success rate is calculated as 1−(1−P)Nsite

Supplementary Figure 3 Multiple-probability fluctuation analysis of glutamate imaging at a synapse with Nsite of 9.

a Variance–mean plot of fluorescence response of eEOS. Glutamate release was evoked under various [Ca2+]e conditions: light green,1 mM; green, 1.125 mM; cyan, 1.25 mM; blue, 1.5 mM; white, 2 mM; red, 4 mM [Ca2+]e plus 4-AP (n = 50 events each). Variance values of amplitudes under individual conditions are plotted against mean values. The dotted line shows a parabolic fit using a binomial model of glutamate release. Error bars indicate theoretical estimates of standard errors of the variance using h-statistics. b Histogram analysis of fluorescence responses of eEOS evoked by a single stimulus under conditions of multiple release probabilities (n = 50 events each). The color code for [Ca2+]e is the same as in a. Dashed lines show binomial release model distributions generated with quantal parameters estimated by multiple-probability fluctuation analysis in a. N site  = 9, Q = 3.9 %, P = 0.03, 0.09, 0.03, 0.12, 0.18, and 0.70, respectively. Background noise SD of 0.5 % and quantal variability (CV = 0.28) were also taken into account for the distribution. Cramér–von Mises test was used for testing goodness-of-fit. P = 0.064 (T = 0.42) for 1 mM [Ca2+]e, P = 0.61 (T = 0.095) for 1.125 mM [Ca2+]e, P = 0.065 (T = 0.42) for 1.25 mM [Ca2+]e, P = 0.48 (T = 0.12) for 1.5 mM [Ca2+]e, P = 0.97 (T = 0.031) for 2 mM [Ca2+]e, and P = 0.38 (T = 0.15) for 4 mM [Ca2+]e plus 4-AP. c Relationship between expected and observed success rates of glutamate release. The color code for [Ca2+]e is the same as in a

Supplementary Figure 4 Immunocytochemical analysis of AZ proteins in Munc13-1 or RIM1 knockdown synapses.

a Representative immunofluorescence images of major AZ proteins, including Munc13-1, RIM1, bassoon, piccolo, and ERC1b/2, in control, Munc13-1 shRNA lentivirus-infected neurons and RIM1 shRNA lentivirus-infected neurons. Scale bar, 5 µm. Images are representative of 4 experiments. b A summary graph showing the average immunofluorescence intensity of AZ proteins at synapses (n = 60 synapses each from 4 culture preparations). Lentiviral expression of Munc13-1 shRNA reduces the immunofluorescence intensity of Munc13-1 to 11% of control. Lentiviral expression of RIM1 shRNA reduces the immunofluorescence intensity of RIM1 and of Munc13-1 to 18% and 48% of control, respectively. Data shown are mean ± SEM. Two-tailed Wilcoxon rank sum test was used for statistical analysis. Munc13-1: P = 1.7×10−17(W = 3423) for control v.s. shMunc13-1, P = 0.000013 (W = 2632) for control v.s. shRIM1; RIM1: P = 0.14 (W = 2083.5) for control v.s. shMunc13-1, P = 1.1×10−17 (W = 3431) for control v.s. shRIM1; Bassoon: P = 0.15 (W = 1525) for control v.s. shMunc13-1, P = 0.23 (W = 1570) for control v.s. shRIM1; Piccolo: P = 0.59 (W = 1904) for control v.s. shMunc13-1, P = 0.026 (W = 2226) for control v.s. shRIM1; Erc1b/2: P = 0.59 (W = 1698) for control v.s. shMunc13-1, P = 0.16 (W = 1530) for control v.s. shRIM1. **P < 0.001; †0.01< P < 0.05; n.s., not significant, P > 0.05.

Supplementary Figure 5 Quality control for STORM imaging.

a Images of Munc13-1 immunofluorescence labeling using a monoclonal antibody (clone: 11B-10G) at three different concentrations. Scale bar, 5 µm. Images are representative of 2 experiments. b Titration curve of Munc13-1 monoclonal antibody (clone: 11B-10G) for staining of synaptic Munc13-1. Each data point results from 60 synapses, except for the highest condition (the rightmost data point) which results from 120 synapses. Data shown are mean ± SEM. Practical experiments were performed at 500 ng/mL (a concentration at which most epitopes are saturated with primary antibodies). c,d 3D-STORM images of Munc13-1 immunostained with monoclonal Munc13-1 antibody (clone: 11B-10G) and Alexa Fluor 647-labeled secondary antibody. Shown are images reconstructed from the initial 25,000 frames of data acquisition (c) and from the subsequent 25,000 frames of data acquisition (d). Bottom row of images shows enlarged view of the white-boxed region in the top panels. Scale bars, 2 µm (top) and 200 nm (bottom). The z-positions are color-coded based on the colored scale bar. In our experimental conditions, 3D-STORM imaging with Alexa Fluor 647-labeled antibodies provided high reproducibility of image reconstruction for analyzing nanoscale molecular architecture. Images are representative of 13 experiments repeated with 8 culture preparations.

Supplementary Figure 6 3D-STORM imaging of Munc13-1 using monoclonal antibodies.

a A domain structure of Munc13-1 and epitope sites for the Munc13-1 monoclonal antibodies used in this study are shown. b, c Conventional microscopy images (top) and 3D-STORM images (bottom) of Munc13-1 immunostaining with monoclonal antibodies 2A-5 (b) and 5D-7G (c). Scale bars, 1 µm. The z-positions are color-coded based on the colored scale bar. Images are representative of 3 (b) and 2 (c) experiments, respectively. As seen in 3D-STORM imaging using the monoclonal antibody 11B-10G (Fig. 4 and Supplementary Figure 4), nanoscale discrete spots of Munc13-1 at the subsynaptic level are also observed using these two monoclonal antibodies.

Supplementary Figure 7 Reduced localization of syntaxin-1 at Munc13-1 knockdown synapses.

a, b Immunofluorescence images of bassoon (red) and syntaxin-1 (cyan) of control (a) and Munc13-1 knockdown neurons (b). Scale bar, 5 µm. Cells were fixed with 1% paraformaldehyde (PFA) on ice and permeabilized with saponin. Arrowheads indicate synaptic sites identified by bassoon immunofluorescence. Synaptic syntaxin-1 immunofluorescence was clearly observed in control neurons. Images are representative of 4 (a) and 2 (b) experiments repeated, respectively. c Quantification of syntaxin-1 immunofluorescence intensity at control and Munc13-1 knockdown neurons (n = 90 ROIs, respectively). “S” and “N” denote synaptic and non-synaptic, respectively. Data are represented as mean ± SEM. Two-tailed Wilcoxon rank sum test was used for statistical analysis. P = 2.6×10−7 (95% confidence interval 0.32 to 0.66, W = 5850) for controls; P = 0.13 (95% confidence interval −0.031 to 0.26, W = 4584) for Munc13-1 knockdown. **P < 0.001; n.s., not significant, P > 0.05.

Supplementary Figure 8 Reconstitution of Munc13-1/syntaxin-1 macromolecular assemblies in non-neuronal cells.

a Fluorescence images of Munc13-1-EGFP expressed in 293T cells in the absence (left) or prescence (right) of a phorbol ester, PMA. Munc13-1 molecules were translocated to the cell membrane and formed macromolecular self-assemblies with PMA application. Scale bar, 10 µm. Images are representative of 3 experiments. b Fluorescence images of Munc13-1-EGFP (left) and TagRFP-ZF-CAAX (middle) co-expressed in a 293T cell. Right panel shows a merged image. Munc13-1-EGFP and TagRFP-ZF-CAAX form macromolecular self-assemblies at the cell membrane. TagRFP-ZF-CAAX expression alone does not form macromolecular assemblies (data not shown). Scale bar, 10 µm. Images are representative of 4 experiments. c Fluorescence images of syntaxin-1A-pHluorin (left) and TagRFP-ZF-CAAX (middle) expressed in a COS7 cell. Right panel shows a merged image. Munc13-1 and Munc18-1 were also expressed in this experiment. Scale bar, 10 µm. Images are representative of 5 experiments.

Supplementary Figure 9 Detection and quantification of spontaneous glutamate release events.

a Detection rate of spontaneous glutamate release events plotted against detection threshold values. Gray lines represent the results for individual synapses, and white circles represent the averaged result. The detection rates of release events were nearly constant within a range of thresholds (1.8 to 2.5). A detection threshold value of 2.0 was used for the analysis in Fig. 1. The red dotted line represents the false positive rate estimated from simulated background noise, and the blue dotted line represents the false negative rate that is estimated by subtracting data by the false positive rate. b The estimated mean signal amplitude of successful events plotted against detection threshold values. Gray lines represent the results for individual synapses, and white circles represent the averaged result.

Supplementary Figure 10 Synaptic glutamate responses of eEOS in the presence of free glutamate.

a Time course of fluorescence responses of eEOS at a synapse evoked by 20 stimuli at 50 Hz in 4 mM [Ca2+]e plus 20 µM 4-AP and 100 µM DL-TBOA. Left and right traces are in the absence and presence of glutamate, respectively; average of five trials. Orange dots denote the timing of the stimulus. b Quantification of fluorescence responses (n = 12 synapses from three culture preparations). Data are represented as mean ± SEM. Two-tailed Wilcoxon rank sum test, 95% confidence interval −1.98 to 0.33, W = 17, P = 0.092.

Supplementary Figure 11 Analysis of quantal fluctuations during high frequency stimulus trains.

a Fluorescence responses of eEOS at a synapse evoked by trains of eight stimuli at 20 Hz are plotted against the stimulus number. Black and gray lines represent averaged and individual responses to 40 trains, respectively. Representative data from 24 synapses. b Responses to each stimulus during the stimulus trains obtained by deconvolution of eEOS fluorescence responses shown in a. Gray lines represent individual responses. Mean (thick lines, upper panel) and variance (thick lines, lower panel) of the responses to each stimulus are calculated. c Plot of variance–mean relation of responses to the succeeding stimuli during 20 Hz stimulus trains (gray triangles, each of which corresponds to each of 2nd to 8th stimulus) are superimposed on the plot of variance–mean relation of responses to the isolated stimuli—stimuli without immediately preceding stimuli—under three different conditions (black circles): 1st stimuli of trains of eight stimuli at 2 mM [Ca2+]e, single stimuli at 1 mM [Ca2+]e, and single stimuli at 4 mM [Ca2+]e plus 4-AP (n = 40 events each). Variance values of amplitudes under individual conditions are plotted against mean values. Error bars indicate theoretical estimates of standard errors of the variance using h-statistics. A parabolic fit with the binomial model (dashed curve) was applied to data for the isolated stimuli, providing N site  = 9.1, Q = 3.4 %, P = 0.07, 0.23, and 0.77, respectively. Note that the variance–mean data for the succeeding stimuli appear to have good fit to the parabolic curve. d Effect of prestimulus fluorescence levels attained by preceding stimuli on quantal fluctuation of the responses evoked by succeeding stimuli. The relative quantal fluctuation was calculated by dividing the variance estimate for the succeeding stimuli (2nd to 8th stimuli during the course of 20 Hz trains) by the expected variance in the binomial model fitted for the isolated stimuli as in c, and plotted against the prestimulus fluorescence levels (gray points). To clarify the dependence on the prestimulus fluorescence levels, the data were stratified into five groups in 4% increments and averaged (purple, 0–4%, n = 31 data points; blue, 4–8%, n = 69; green, 8–12%, n = 43; orange, 12–16%, n = 12; red, >16%, n = 13). The result was obtained from n = 24 synapses from 8 experiments. Data are represented as mean ± SEM.

Supplementary Figure 12 The effect of probe saturation on variance–mean relationship and quantal estimates.

a Simulated fluorescence responses for glutamate sensors with variable dissociation constants (k) (see Methods). b Variance–mean relation of saturable fluorescence responses (thick curves). We set N = 20 and Q′ = 5% with variable values of saturation index, s (s = 0,0.1,0,2,0,5,1.0,2.0, corresponding to k = ∞,1000,500,200,100,50, respectively). Dashed curves represent fits with conventional binomial model. c Dependence of the estimated values of quantal parameters (N and Q) by the conventional binomial model fit on the saturation index, s. The maximum synaptic response is also shown. d Normalized variance–mean relationship under variable s values. Simulated data in b was normalized with parameters estimated by the conventional binomial fit (dotted curves in b). e Normalized variance–mean relationship for the combined experimental data from ten selected synapses having large (>8) N values. The curve shows the fit by the model with saturation, in which s was treated as a free parameter. However, it should be noted that the fit yielded s value of almost zero (0.0). The lower panel shows the Akaike Information Criterion (AIC) for model fits with s set at various values. f Normalized variance–mean relationship for the combined experimental data for all 53 synapses. The curve shows the model fit as in e; the fit also yielded near zero value of s. The lower panel shows AIC for model fits with fixed variable s values.

Supplementary Figure 13 Evaluation of localization precision in 3D-STORM imaging experiments.

Histograms of the 3D localization distribution of Alexa-647 molecules are shown. Alexa-647 labeled antibodies were non-specifically bound on the fixed neuronal cell cultures and imaged in STORM imaging buffer. Localizations from 24 non-specifically bounded antibodies (within 500 nm of the focal plane) were aligned by their center of mass to collectively evaluate the localization precision. The Gaussian function was fit to each histogram, yielding standard deviations of 9.0 nm in x-axis, 9.7 nm in y-axis, and 19.0 nm in z-axis, respectively.

Supplementary information

Videos

Supplementary Video 1 | Imaging of glutamate release at synapses

eEOS fluorescence responses (glutamate signals) in response to single electrical stimulus are shown (total of 10 trials). Trial-to-trial variation characterized by frequent failures of release can be seen. Scale bar, 5 µm.

Supplementary Video 2 | Munc13-1 nanoassemblies at the AZ

3D-STORM images of Munc13-1 (yellow) and bassoon (red). Munc13-1 and bassoon were immunostained with Alexa Fluor 647–labeled secondary antibody and DyLight 755–labeled secondary antibody, respectively.

Supplementary Video 3 | Munc13-1/syntaxin-1 supramolecular assemblies at the AZ.

3D-STORM images of Munc13-1 (yellow) and syntaxin-1A (blue). Munc13-1 and syntaxin-1A were immunostained with Alexa Fluor 647/405-labeled secondary antibody and Alexa Fluor 647/488-labeled secondary antibody, respectively. Scale bar, 200 nm.

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Sakamoto, H., Ariyoshi, T., Kimpara, N. et al. Synaptic weight set by Munc13-1 supramolecular assemblies. Nat Neurosci 21, 41–49 (2018). https://doi.org/10.1038/s41593-017-0041-9

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