Figures and data in Rapid regulation of vesicle priming explains synaptic facilitation despite heterogeneous vesicle:Ca2+ channel distances

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11 figures, 6 tables and 2 additional files

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Figure 1 with 1 supplement

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Deriving the spatial docked SV distribution.

(A) Example EM image of an NMJ active zone (AZ) obtained from a 3^rd instar *Drosophila* larva expressing the dominant Unc13A isoform after high pressure freeze fixation (Unc13A rescue: *elav-GAL4/+;;UAS-Unc13A-GFP/+;P84200/P84200*). The image captures a T-bar cross section. For clarity, the T-bar is colored in light blue, SVs are indicated with circles, the outline of the presynaptic plasma membrane is shown (magenta). Docked SVs are marked with black circles (non-docked in magenta). Black scale bar: 50 nm. (B) Histogram of the distances of docked SVs to the T-bar center obtained from EM micrographs 19 SVs observed in n = 10 EM cross-sections/cells from at least two animals, the same distance measurements had previously been used for the analysis depicted in Figure 5 of Reddy-Alla et al. (2017). The solid green line is the fitted Rayleigh distribution (σ = 76.5154 nm, mean is 95.9 nm, standard deviation, SD is 50.1 nm). (C) The one-dimensional Rayleigh distribution (green line) is integrated in order to estimate the docked SV distance distribution in the whole presynapse. (D) The integrated Rayleigh distribution is more symmetric, and the mean increases to 122.1 nm. SD is 51.5 nm. (E) The three left example images show wildtype (*w[1118]*) AZs stained against Unc13A and imaged on a STED microscope. The right hand image shows the average fluorescence signal for 524 individual centered AZ images from 16 different NMJs and more than three different animals (see Materials and methods for details). White scale bars: 100 nm. (F) Histogram of fluorescence intensities against distance from the AZ center, as derived from the average STED image plotted together with the integrated Rayleigh distribution derived from the EM analysis (replotted from panel D), showing a close agreement between the two approaches. Additional EM analysis of wildtype flies and the analysis of an independent STED experiment are compared to the data depicted here in Figure 1—figure supplement 1. Used genotype: Unc13A rescue (panel A, B), *w[1118]* (panel E, F). Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all genotypes. Raw data corresponding to the depicted histograms can be found in the accompanying source data file (Figure 1—source data 1). Scripts used for analysis of average STED image and plotting of histograms in 1B and 1F can be found in accompanying source data zip file (Figure 1—source data 2).

Figure 1—source data 1 Source data for graphs in Figure 1 and Figure 1—figure supplement 1.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig1-data1-v2.xlsx
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Figure 1—source data 2 Matlab codes used for data analysis, original images, and instructions for analysis depicted in Figure 1 and Figure 1—figure supplement 1.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig1-data2-v2.zip
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Figure 1—figure supplement 1

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EM + STED vesicle positions are consistent between independent datasets and overlapping with each other.

(A) Histogram (blue) of the distances of docked SVs to the T-bar center obtained from EM micrographs of Wild-type (*w[1118]*) animals (‘EM dataset 1’) plotted with a fitted Rayleigh distribution green, N = 5 animals, n = 11 AZs, mean of Rayleigh distibution = 92.83 nm, SD is 48.5 nm; the same distance measurements had been used for the analysis depicted in Figure 6 of Böhme et al. (2016). (B) Integrated distributions of ‘EM dataset 2’ (Figure 1B, Unc13A rescue, black) with a mean of 122.1 nm and SD of 51.5 nm and of ‘EM dataset 1’ with a mean of 118.9 nm (blue) and SD of 49.9 nm. (C) Average images of ‘STED dataset 1’ (replotted from Figure 1E, green box) (N = 3 animals, n = 524 AZs) and ‘STED dataset 2’ (red box) (N = 3 animals, n = 586 AZs). (D) Overlay of the distance distributions derived from all four (two EM and two STED) datasets. Used genotypes: *w[1118]* (‘EM dataset 2’, panel A-D), Unc13A rescue: *elav-GAL4/+;;UAS-Unc13A-GFP/+;P84200/P84200* (‘EM dataset 1’, panel B, D). Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes.

Figure 2 with 3 supplements

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Characterization of short-term plasticity at the *Drosophila melanogaster* NMJ.

Two-electrode voltage clamp recordings of AP-evoked synaptic transmission in muscle 6 NMJs (genotype: *Ok6-GAL4/+* (*Ok6-Gal4/II* crossed to *w[1118]*)). Left panel (**A, C, E**) shows example traces from one cell. Right panel (B, D, F) shows quantification across cells. (A) Representative eEJC traces from a single cell measured at different Ca²⁺ concentrations (0.75–10 mM). (B) Average eEJC₁ amplitudes and SD from six animals as a function of extracellular Ca²⁺ concentration. (C) Representative eEJC traces of paired pulse paradigm (10 ms inter-stimulus interval, normalized to eEJC₁) from single cell measured at different Ca²⁺ concentrations (0.75–10 mM). While STF can be seen at the two lowest extracellular Ca²⁺ concentrations (0.75 and 1.5 mM), the cell exhibits STD for extracellular Ca²⁺ concentrations of 3 mM or more. Insert (gray background) shows calculation of eEJC₂. An exponential function was fitted to the decay to estimate the baseline for the second response (see Figure 1—figure supplement 1 and Materials and methods for details). (D) Mean and SD of PPR values (6 cells from six animals) at different Ca²⁺ concentrations. (E) Experiment to assess variance of repeated synaptic responses in a single cell. eEJC₁ traces in response to nine consecutive AP stimulations (10 s interval) are shown (orange lines) together with the mean eEJC₁ response (black line) at different extracellular Ca²⁺ concentrations (0.75–10 mM, see Materials and methods). (F) Plot of mean eEJC₁ variance as a function of the mean eEJC₁ amplitude across 6 cells from six animals for each indicated Ca²⁺ concentration. The curve shows best fitted parabola with intercept forced at (0,0) (Var = −0.0061*<eEJC₁>²+0.6375 nA*<eEJC₁>, corresponding to n_sites = 164 and q = 0.64 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). For the variance-mean relationship of the single cell depicted in Figure 2E , please refer to Figure 2—figure supplement 2. Experiments were performed in *Ok6-Gal4/+* 3^rd instar larvae, often used as a control genotype for experiments using cell-specific driver lines. Separate experiments were performed to ensure that this genotype showed similar synaptic responses and STP behavior as wildtype animals (Figure 2—figure supplement 3). Used genotype: *Ok6-Gal4/II* crossed to *w[1118]*. Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes. Data points depict means, error bars are SDs across cells except in (F), where error bars show SEM. Raw data corresponding to the depicted graphs can be found in the accompanying source data file (Figure 2—source data 1). Scripts for analysis of recorded traces are found in accompanying source data zip file (Figure 2—source data 2). Raw traces from paired-pulse experiments summarized in Figure 2 and Figure 2—figure supplements 2 and 3 can be found in Figure 2—source data 2; Figure 2—figure supplement 1—source data 1; Figure 2—figure supplement 3—source data 1. Estimation of eEJC₂ amplitudes and fitting of a smooth mEJC function (used in simulations, see Materials and methods) are illustrated in Figure 2—figure supplement 1.

Figure 2—source data 1 Raw data for experiments displayed in Figure 2 and Figure 2—figure supplement 2.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig2-data1-v2.zip
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Figure 2—source data 2 Matlab code used for data analysis of electrophysiological traces.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig2-data2-v2.zip
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Figure 2—source data 3 Raw data which was used for depicted anaylsis in Figure 2 and Figure 2—figure supplement 3.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig2-data3-v2.xlsx
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Figure 2—figure supplement 1

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Illustration of analysis of experimental electophysiological data.

(A) Analysis of eEJCs. The eEJC₁ amplitude is determined as the first minimum within 10 ms of the stimulus. The eEJC₂ amplitude is determined from the baseline found by exponential extrapolation of the eEJC₁ decay. (B) The mean mEJC from experimental recordings and the best fit used for convolution (see Materials and methods). Used genotype: *Ok6-Gal4/II* crossed to *w[1118]*. Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes.

Figure 2—figure supplement 1—source data 1 Raw data for mEJC recordings used for simulations in Figure 2—figure supplement 1.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig2-figsupp1-data1-v2.zip
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Figure 2—figure supplement 2

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Illustration of fluctuation analysis (quantification across cells shown in Figure 2F) in a single representative cell.

(A) Example traces showing nine individual stimulation sweeps (orange) per Ca²⁺ concentration (0.75–10 mM). Averages of single sweeps are shown in black. (B) Quantification of eEJC amplitudes of single sweeps (orange) at different Ca²⁺ concentrations. Scattering of these values illustrates the variance of eEJC amplitudes between individual sweeps. Average eEJC amplitudes per Ca²⁺ concentration are indicated in black, error bars show SDs. Average amplitudes (and their variance) shown here were used in C. (C) Variances of eEJC amplitudes in this cell (from nine repetitions per Ca²⁺ concentration, indicated in blue) plotted as a function of the mean eEJC amplitude. A parabola can be fitted to the data points (forced through (0,0) intercept, see Materials and methods for futher information and exact genoytpes). Used genotype: *Ok6-Gal4/II* crossed to *w[1118]*. Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes.

Figure 2—figure supplement 3

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Electrophysiological comparison of synaptic transmission in wildtype (*w[1118], +/+*) (black) and *Ok6-Gal4/+* (orange) flies.

Electrophysiological recordings of muscle 6 NMJs upon a paired-pulse stimulation (10 ms inter-stimulus interval) at 0.75 mM (**A-D**) and 1.5 mM Ca²⁺(**E-H**). (A) Representative example traces for eEJC₁ from single cells in *+/+* or *Ok6-Gal4/+*. (B) Quantification of eEJC₁ amplitudes in *+/+* (n = 6 cells from three animals) and *Ok6-Gal4/+* (n = 8 cells from four animals), averages and SDs across cells are indicated. (C) Representative normalized eEJC example traces of paired pulse (10 ms inter-stimulus interval) responses in representative cells of +/+ and *Ok6-Gal4/+* animals. (D) Quantification of paired pulse ratios (PPRs) in *+/+* (n = 6 cells from three animals) and *Ok6-Gal4/+* (n = 8 cells from four animals), averages across cells and SDs are indicated. (E) Representative example traces for eEJC₁ from single cells of *+/+* or *Ok6-Gal4/+* animals. (F) Quantification of eEJC₁ amplitudes in *+/+* (n = 5 cells from three animals) and *Ok6-Gal4/+* (n = 5 cells from three animals), averages and SDs across cells are indicated. (G) Normalized eEJC example traces of paired pulse (10 ms inter-stimulus interval) from single cells in *+/+* and *Ok6-Gal4/+* animals. (G) Quantification of PPRs in *+/+* (n = 5 cells from three animals) and *Ok6-Gal4/+* (n = 5 cells from three animals), averages across cells and STDs are indicated. Used genotypes: *Ok6-GAL4/+* (*Ok6-Gal4/II* crossed to *w[1118]*) and +/+: *w[1118]*. Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes.

Figure 2—figure supplement 3—source data 1 Raw data for experiments displayed in Figure 2—figure supplement 3.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig2-figsupp3-data1-v2.zip
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Figure 3 with 2 supplements

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Simulation of AP-induced synaptic Ca²⁺ profiles.

(A) Estimation of the simulation volume and Ca²⁺ simulations. The left hand image shows a confocal scan of a 3^rd instar larval NMJ stained against the AZ marker Bruchpilot (BRP) (genotype: *w[1118]; P{w[+mC]=Mhc-SynapGCaMP6f}3–5* (Bloomington Stock No. 67739). The right hand image shows a higher magnification of the indicated region. To determine the dimensions of the simulation volume, the average distance of each AZ to its closest four neighboring AZs (k-NND = *k^th* nearest neighbor distance) was determined. The average inter-AZ distance to each of the closest four neighboring AZs (1- through 4-NND) is depicted on the left. Average and SEM of inter-AZ distances (1-4-NND) are depicted on the right. White scale bars: Left: 5 µm; right: 1 µm. (B) Example illustration of the Ca²⁺ simulation. The simulation volume is a cylinder whose base area (radius 624 nm) is the same as a square with side length of the mean 1–4-NND. The local Ca²⁺ concentration is shown at different time points following an AP-induced Gaussian Ca²⁺ current (the area/height is a free parameter, see Table 2, the FWHM is 0.36 ms). The simulation started at t=0 ms, Ca²⁺ influx was initiated at t=0.5 ms and peaked at t=2 ms. The Ca²⁺ (point) source is located in the AZ center (black dot) and the Ca²⁺ concentration is determined at 10 nm height from the plasma membrane. (C) Example simulation of the local Ca²⁺ concentration profile in response to stimulation with a pair of APs (current was initiated at 0.5 and 10.5 ms and peaked at 2 and 12 ms). Simulations were performed using the best fit parameters of the single sensor model described below (see Figure 4, Table 2). Top left: Ca²⁺ transients in response to the first AP at two distances: 95.9 nm and 122.1 nm (the mean of Rayleigh/integrated Rayleigh). Top right: AP-induced Ca²⁺ transient at 122.1 nm for all experimental extracellular Ca²⁺ concentrations. Bottom left: Semi-logarithmic plot of Ca²⁺ decays toward baseline after the 2^nd transient (residual Ca²⁺) at different extracellular Ca²⁺ concentrations ([Ca²⁺]_ext). Time constant of decay is τ = 111 ms. Bottom right: Residual Ca²⁺ levels at 122.1 nm after 10.5 ms of simulation as a function of extracellular Ca²⁺ concentrations. Data depicted in panel A were collected from 17 different animals. Used genotype: *w[1118]; P{w[+mC]=Mhc-SynapGCaMP6f}3–5* (Bloomington Stock No. 67739, panel A). Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes. Values used for graphs can be found in the accompanying source data file (Figure 3—source data 1). GCaMP6m experiment is summarized in Figure 3—figure supplement 1. Ca²⁺ signals for all optimised models (below) are summarised in Figure 3—figure supplement 2.

Figure 3—source data 1 Average cell-wise mean fluorescence values and fit parameters of hill-curve fit on presynaptic GCaMP data, and NND values.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig3-data1-v2.xlsx
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Figure 3—figure supplement 1

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Experiment to determine the dependence of AP-induced Ca²⁺ influx on the extracellular Ca²⁺ concentration.

(A) Example frame of maximum fluorescence during recording of presynaptic GCaMP6m at 6 mM extracellular Ca²⁺. Red dotted line indicates the ROI used for read-out of the fluorescence signal. (B) 10 s fluorescence trace of experiment shown in A. At the 5 s mark, 20 APs are given over 1 s. Subtracting the fluorescence at 4.75 s from the maximum fluorescence gives the value dF plotted in panel D. (C) Baseline-subtracted fluorescence (see Materials and methods for details) traces of 5 different animals over the whole range of extracellular Ca²⁺ concentrations. 8.3 mM EGTA was added at the end to quench Ca²⁺ influx. (D) Quantification of dF (see panel B) per cell and Ca²⁺ concentration. The nonlinear fit with hill coefficient, m, of 2.43 (as previously determined for GCaMP6m Barnett et al., 2017) is indicated as a dashed black line, see Materials and methods for details. Mean is shown as black bars ± SEM. Used genotype: *w[1118]; P{y[+t7.7] w[+mC]=20XUAS-IVS-GCaMP6m}attP40 crossed to Ok6-GAL4*. Materials and methods section ‘Fly husbandry, genotypes and handling’ lists all exact genotypes. Data summary as well as best fit Hill curve corresponding to the depicted graph can be found in the accompanying source data file (Figure 3—source data 1).

Figure 3—figure supplement 2

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Ca²⁺ profiles of all models using best fit parameters (reported in Table 1; Table 2).

Left: Both transients at 1.5 mM extracellular Ca²⁺ concentration at 95.9 nm and 122.1 nm. Middle: For all experimental extracellular Ca²⁺ concentrations an AP induced Ca²⁺ transient at a distance of 122.1 nm distance from the Ca²⁺ source is shown. Right: Semilogarithmic plot of Ca²⁺ decays at the different extracellular Ca²⁺ concentration. Time constant of decay is τ = 111 ms in all models. Plots of Ca²⁺ in the single-sensor model are the same as Figure 3C. Parameters can be found in Tables 1,2.

Figure 4 with 1 supplement

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A single-sensor model reproduces the magnitude of transmission to single APs, but cannot account for STF and variances.

(A) Diagram of the single-sensor model. Consecutive binding of up to 5 Ca²⁺ ions to a vesicular Ca²⁺ sensor increases the probability of SV fusion (transition to state F) indicated by the color of the state. Primed SVs can be replenished from an infinite Vesicle pool. (B) Experimental eEJC traces averaged over all cells (black) together with average simulated traces (red). (C) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show the standard deviations of data (see text) and simulations, respectively. Simulations reproduce eEJC₁ amplitudes well. (D) Average (over all cells), normalized eEJC traces of experiment (black) and simulation (red). Simulations obtained with this model lack facilitation, as indicated by the red symbols. (E) PPR values of experiment (gray) and best fit simulation (blue). Green curve show simulations with replenishment 100x slower than the fitted value illustrating the effect of replenishment on the PPR. Error bars and colored bands show standard deviation. Best fit simulations do not reproduce the facilitation observed in the experiment at low extracellular Ca²⁺ concentrations. (F) Average simulated traces (red) and examples of different outcomes of the stochastic simulation (colors). (G) Plot of the mean synaptic variance vs. the mean eEJC₁ amplitudes, both from the experiment (black) and the simulations (red). The curves show the best fitted parabolas with forced intercept at (0,0) (simulation: Var = −0.0041*<eEJC₁>²+0.5669 nA*<eEJC₁>, corresponding to n_sites = 244 and q = 0.57 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). Simulations reveal too much variance in this model. Experimental data (example traces and means) depicted in panels B-E,G are replotted from Figure 2A–D,F. All parameters used for simulation can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 4—source data 1). Exploration of the difference between PPR estimations in deterministic and stochastic simulations are illustrated in Figure 4—figure supplement 1.

Figure 4—source data 1 Simulation data for graphs in Figure 4C, G, E and Figure 4—figure supplement 1.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig4-data1-v2.xlsx
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Figure 4—figure supplement 1

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Stochastic and deterministic simulations yield different PPR values.

PPR values from stochastic (bullets) and deterministic (curves) simulations of the single-sensor model (Figure 4) at varying amounts of Ca²⁺ influx. Simulations are performed with (blue) and without (red) replenishment. Decreasing Ca²⁺ influx increases the PPR values due to less SV depletion. Stochastic simulations generally yield higher PPR estimations than the deterministic simulations. The effect is most significant at the lower Ca²⁺ influx. Parameters used for simulation can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means) can be found in the accompanying source data file (Figure 4—source data 1).

Figure 5

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Analysis of the spatial dependence of SV fusion in the single-sensor model reveals a near-identical use of release sites during the two APs, thereby favoring STD.

(A) Two examples of docked SVs stochastically placed according to the distribution described in Figure 1D and their behavior in the PPR simulation at 0.75 mM extracellular Ca²⁺. For clarity, 10 SVs are shown per AZ (the actual number is likely lower) and only a central part of the AZ is shown. Top row: Prior to AP₁ SVs are primed (dark gray circles) and pV_r1 is indicated as numbers. The larger dashed, blue circle in the AZ center indicates pV_r1 = 0.25. Second row: After AP₁ some of the SVs have fused (dashed blue circles). Third row: Right before AP₂ some of the SVs that had fused in response to AP₁ have been replenished (orange shading), and pV_r2 is indicated as a number. The larger dashed, red circle indicates pV_r2 = 0.25. Bottom row: After AP₂ the second release has taken place. Small dashed circles indicate release from AP₁ and AP₂ (blue and red, respectively). The small increase in pV_r caused by Ca²⁺ accumulation cannot produce facilitation because of depletion of SVs. (B) The average simulation at the same time points as in (A). Histograms represent primed SVs (black and gray) as well as first and second release (blue and red) illustrating how release from AP₁ and AP₂ draw on the same subpopulation of SVs. The blue and red curves indicate the vesicular release probability as a function of distance during AP₁ (blue) and AP₂ (red). The green arrows show the repopulation of previously used sites via replenishment. AP₂ draws on the same portion of the SV distribution as AP₁ causing depression despite the fast replenishment mechanism. Parameters used for simulations can be found in Tables 1–3.

Figure 6 with 1 supplement

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A dual fusion-sensor model of Ca²⁺ sensors cooperating for SV fusion improves STP behavior, but suffers from too little STF, asynchronous release and too much variance.

(A) Diagram of the dual fusion-sensor model (left). A second Ca²⁺ sensor for fusion with slower kinetics can increase pV_r (indicated by color of each Ca²⁺ binding state). The second fusion sensor is assumed to act on the energy barrier in a similar way as the first sensor (right). The top right equation shows the relation between the fusion constant, *k_fuse*, and energy barrier modulation with n and m being the number of Ca²⁺ bound to the first and second Ca²⁺ sensor, respectively. Ca²⁺ binding to the second sensor is described by similar equations as for the first sensor, but with different rate constants and impact on the energy barrier. (B) Simulation of Ca²⁺ binding to the fast (blue) and slow (other colors) Ca²⁺ sensor in simulations at 0.75 mM extracellular Ca²⁺ with different k₂ values but with constant affinity (i.e. fixed ratio of k_-2/k₂). The binding is normalized to the maximal number of bound Ca²⁺ to each sensor (5 and 2, respectively). For illustration purposes in this graph the fusion rate was set to 0 (because otherwise the fast sensor (blue line) would be consumed by SV fusion). k₂ = 4e7 M^-1s^-1 (red trace) illustrates the situation for the optimal performance of the model (approximately best fit value). (C) PPR values in stochastic simulations with the same parameter choices as in (B) but allowing fusion. (D) Experimental eEJC traces (black) together with average simulated traces (red). Simulations show too much asynchronous release compared to experiments. (E) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show standard deviations of data and simulations, respectively. Simulations reproduce eEJC₁ amplitudes well. (F) Average, normalized eEJC traces of experiment (black) and simulation (red). Simulations show too little facilitation compared to experiment. (G) PPR values of experiment (gray) and simulation (blue). Error bars and colored bands show standard deviation. Simulations show too little facilitation compared to experiment. (H) Average simulated traces (red) and examples of different outcomes of the stochastic simulation (colors). (I) Plot of the mean synaptic variance vs. the mean eEJC₁ values, both from the experiment (black) and the simulations (red). Curves are the best fitted parabolas with forced intercept at (0,0) (simulation: Var = −0.0034*<eEJC₁>²+0.5992 nA*<eEJC₁>, corresponding to n_sites = 294 and q = 0.60 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). Simulations lead to too much variance at the highest Ca²⁺ concentrations. (J) Parameter exploration of the second sensor varying the parameters *Q_max*, k₂, and s. Each ball represents a choice of parameters and the color indicates the average PPR value in stochastic simulations with 0.75 mM extracellular Ca²⁺. None of the PPR values match the experiment (indicated by the black arrow). Black lines show the best fit parameters. (K) Same parameter choices as in (I). The colors indicate the number of RRP SVs in order to fit the eEJC₁ amplitudes at the five different experimental Ca²⁺ concentrations. Black lines show the best fit parameters, and arrows show the experimental and best fit simulation values. Note that the best fit predicted more release sites than fluctuation analysis revealed in the experiment. Experimental data (example traces and means) depicted in panels D-G,I are replotted from Figure 2A–D,F. Parameters used for simulations can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 6—source data 1). Simulations of the dual fusion-sensor model with cooperativity 5 are summarized in Figure 6—figure supplement 1.

Figure 6—source data 1 Simulation data for graphs in Figure 6B, E, G, I and Figure 6—figure supplement 1B, D, E.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig6-data1-v2.xlsx
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Figure 6—figure supplement 1

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The dual fusion-sensor sensor model with cooperativity 5 (allowing the binding of 5 Ca²⁺ to the second fusion sensor).

(A) Average, experimental eEJC₁ traces (black) together with average simulated traces (red). The higher cooperativity increases the PPR compared to cooperativity 2 (Figure 6), but introduces massive asynchronous release resulting in distorted eEJC shapes. (B) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show standard deviation. Like with the three models described in the main text, simulations of this model reproduces eEJC₁ amplitudes well, but the variance at the higher extracellular Ca²⁺ concentrations is too large. (C) Average, normalized eEJC traces of experiment (black) and simulation (red). Like in (A) the wrong shape of the eEJC is evident. (D) PPR values of experiment (gray) and simulation (blue). Error bars and colored bands show standard deviation. Despite the increase in PPR compared to the dual fusion-sensor model with cooperativity 2, the PPR is still too low. (E) Plot of the mean synaptic variance vs. the mean eEJC₁ values, both from the experiment (black) and the simulation (red). The curves show the best fitted parabolas with forced intercept at (0,0) (simulation: Var = −0.00089*< eEJC₁>²+0.6728 nA*< eEJC₁>, corresponding to n_sites = 1124 and q = 0.67 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). This model leads to an even larger overshoot of the variance than the dual fusion-sensor model with cooperativity 2 (Figure 6). Experimental data (example traces and means) depicted in panels A-E are replotted from Figure 2A–D,F. Parameter values used for simulations can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 6—source data 1).

Figure 7 with 3 supplements

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An unpriming model with Ca²⁺ dependent regulation of the RRP accounts for experimentally observed Ca²⁺ dependent eEJCs, STP and variances.

(A) Diagram of the unpriming model. The rate of unpriming decreases with the Ca²⁺ concentration. All other reactions are identical to the single-sensor model (Figure 4A). (B) Assumed basal Ca²⁺ concentration at different extracellular Ca²⁺ concentrations (red curve) together with the steady-state amount of priming (blue). Increasing basal Ca²⁺ concentration increases priming. (C) The average fraction of occupied release sites as a function of time in simulations with 0.75 mM (green) and 10 mM (gray) extracellular Ca²⁺ concentration. Release reduced the number of primed SVs. At 0.75 mM Ca²⁺, the Ca²⁺-dependent reduction of unpriming leads to ‘overfilling’ of the RRP between AP₁ and AP₂, thereby inducing facilitation. (D) Average experimental eEJC traces (black) together with average simulated traces (red). (E) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show standard deviation. (F) Average, normalized eEJC traces of experiment (black) and simulation (red). (G) PPR values of experiment (gray) and simulation (blue). Error bars and colored bands show standard deviation. Simulations reproduce the experimentally observed facilitation. (H) Average simulated traces (red) and examples of different outcomes of the stochastic simulation (colors). (I) Plot of the mean synaptic variance vs. the mean eEJC₁ values, both from the experiment (black) and the simulations (red). The curves show the best fitted parabolas with forced intercept at (0,0) (simulation: Var = −0.0053*<eEJC₁>²+0.6090 nA*<eEJC₁>, corresponding to n_sites = 189 and q = 0.61 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). (J) Similar to Figure 6J. Parameter exploration of the unpriming model varying *Q_max*, *k_M,prim*, and u (unpriming rate constant). Each ball represents a choice of parameters and the color indicates the PPR value. Black lines show the best fit parameters, and arrows show the experimental and best fit simulation values. (K) Same parameter choices as in (J). The colors indicate the optimal maximal number of SVs (i.e. number of release sites, n_sites) in order to fit the eEJC₁ amplitude at the five different Ca²⁺ concentrations. A large span of PPR values (shown in (J)) can be fitted with a reasonable number of release sites (shown in (K)). Experimental data (example traces and means) depicted in panels D-G,I are replotted from Figure 2A–D,F. Parameters used for simulation can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 7—source data 1). Simulations of the unpriming model with cooperativity two are summarized in Figure 7—figure supplement 1. The site activation model (described later) is introduced and results are summarized in Figure 7—figure supplement 3. Simulations of the unpriming model with various inter-stimulus intervals are summarized in Figure 7—figure supplement 2.

Figure 7—source data 1 Simulation data for graphs in Figure 7E, G, I; Figure 7—figure supplement 1B, D, E; Figure 7—figure supplement 2D, F, H and Figure 7—figure supplement 3.: https://cdn.elifesciences.org/articles/51032/elife-51032-fig7-data1-v2.xlsx
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Figure 7—figure supplement 1

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The unpriming model with cooperativity 2.

(A) Average, experimental eEJC traces (black) together with average simulated traces (red). (B) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show standard deviation. Like with the three models described in the main text, simulations of this model reproduce eEJC₁ amplitudes well. (C) Average, normalized eEJC traces of experiment (black) and simulation (red). (D) PPR values of experiment (gray) and simulation (blue). Error bars and colored bands show standard deviation. Like the unpriming model with cooperativity 5 (Figure 7), this model reproduces the short-term facilitation observed in experiments. (E) Plot of the mean synaptic variance vs. the mean eEJC₁ values, both from the experiment (black) and the simulation (red). The curves show the best fitted parabolas with forced intercept at (0,0)) (simulation: Var = −0.0042*< eEJC₁>²+0.5648 nA*< eEJC₁>, corresponding to n_sites = 238 and q = 0.56 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). Like the unpriming model with cooperativity 5, variances decrease with increasing extracellular Ca²⁺ concentration, although the variances are slightly higher. Experimental data (example traces and means) depicted in panels A-E are replotted from Figure 2A–D,F. Parameter values used for simulations can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 7—source data 1).

Figure 7—figure supplement 2

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A model with Ca2+-dependent release site activation accounts for experimentally observed eEJCs, STP and variances.

(A) Diagram of the site activation mechanism. Three states are introduced: [I], inactive, [D], delay, and [A], activated. SV fusion is only allowed from sites in state [A]. The rate from [I] to [D] is increased by Ca²⁺, whereas the rate from [D] to [A] is slower and independent of Ca²⁺, thereby introducing a delay. All (in)activation reactions are assumed to be reversible. (B) Full site activation model. The Ca²⁺ (un)binding of the SVs follow the same equations as in the single-sensor model and occurs independently of the site (in)activation. Replenishment is allowed into empty release sites regardless of activation status. (C) Average, experimental eEJC traces (black) together with average simulated traces (red). (D) eEJC₁ amplitudes of experiment (black) and simulation (red). Error bars and colored bands show standard deviation. Like with the three models described in the main text, simulations reproduce eEJC₁ amplitudes well. (E) Average, normalized eEJC traces of experiment (black) and simulation (red). (F) PPR values of experiment (gray) and simulation (blue). Error bars and colored bands show standard deviation. Like the unpriming model, simulations reproduce the experimentally observed facilitation. (G) Average simulated traces (red) and examples of different outcomes of the stochastic simulation (colors). (H) Plot of the mean synaptic variance vs. the mean eEJC₁ values, both from the experiment (black) and the simulation (red). The curves show the best fitted parabolas with forced intercept at (0,0) (simulation: Var = −0.0043*< eEJC₁>²+0.5398 nA*< eEJC₁>, corresponding to n_sites = 233 and q = 0.54 nA when assuming a classical binomial model (Clements and Silver, 2000), see Materials and methods). Like in experiments, simulations lead to decreasing variance at the highest Ca²⁺ concentrations. (I) The number of sites in state [I] and [A] (gray and red resp.) in simulations with extracellular Ca²⁺ concentrations of 0.75 mM and 10 mM (solid and dashed resp.). The varying basal Ca²⁺ concentration yield different initial amounts of site activation. The activation of sites mainly occurs between APs because of the delay state. Experimental data (example traces and means) depicted in panels C-F,H are replotted from Figure 2A–D, F. Parameter values used for simulations can be found in Tables 1–3. Simulation scripts can be found in Source code 1. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 7—source data 1).

Figure 7—figure supplement 3

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Simulation based time course predictions of paired-pulse STF recovery for different interstimulus intervals across different Ca2+ concentrations (0.75–10 mM).

(A) Estimated PPRs for 0.75, 1.5, 3, 6 and 10 mM extracellular Ca²⁺ (from top to bottom) as a function of interstimulus interval (5, 10, 25, 50, 100, 250, 500 and 1000 ms). STF can be detected at low (0.75 mM) and physiological (1.5 mM) Ca²⁺ concentrations and decays after approximately 100 ms, no STF can be detected at high (3–10 mM) Ca²⁺ concentrations (starting with PPR values below 0.5 at 5 ms and increasing to PPR values around one for intervals above 25 ms). Regions of interest indicated by dashed red square are shown as a close-up in next panel. (B) Estimated paired-pulse ratio values (PPR) for Ca²⁺ concentrations (0.75–10 mM) 0.75, 1.5, 3, 6 and 10 mM extracellular Ca²⁺ (from top to bottom) as a function of their interstimulus interval (5, 10, 25, 50 ms). (C) Examples of average traces from paired-pulse simulations at different (0.75–10 mM) extracellular Ca²⁺ (from top to bottom) for 5 ms (blue), 10 ms (red), 25 ms (yellow) and 50 ms (purple) interstimulus intervals. Results from simulations (means and SDs) can be found in the accompanying source data file (Figure 7—source data 1).

Figure 8

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The unpriming model counteracts short-term depression by increasing the number of responsive SVs between stimuli and predicts a more efficient use of SVs throughout the synapse.

(A) Two examples of docked SVs stochastically placed according to the distribution described in Figure 1D and their behavior in the PPR simulation at 0.75 mM extracellular Ca²⁺ concentration. For clarity, 10 SVs are shown per AZ and only a central part of the AZ is shown. Top row: Prior to AP₁, only some release sites contain a primed SV (dark gray circles) and pV_r1 is indicated as a number. Initially empty release sites are indicated by dashed black squares. The larger dashed, blue circle in the AZ center indicates pV_r1 = 0.25. Second row: After AP₁ some of the SVs have fused (dashed blue circles). Third row: Right before AP₂ the initially empty sites as well as the sites with SV fusion in response to AP₁ have been (re)populated (orange shading). pV_r2 is indicated as a number. The larger dashed, red circle indicates pV_r2 = 0.25. Bottom row: After AP₂ the second release has taken place. Small, dashed circles indicate release from AP₁ and AP₂ (blue and red resp.). (B) The average simulation at the same time points as in (A). Histograms represent primed SVs (black and gray) as well as first and second release (blue and red) illustrating how release from AP₁ and AP₂ draw on a larger part of the SV distribution (compare to Figure 5) and how the increase in RRP size can induce facilitation. The blue and red curves indicate the vesicular release probability as a function of distance during AP₁ (blue) and AP₂ (red). Parameters used for simulations can be found in Tables 1–3.

Figure 9

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Cartoon illustrations of the single-sensor, the dual fusion-sensor, and the unpriming models during a paired-pulse simulation at 0.75 mM extracellular Ca²⁺.

Top row: SVs primed (white ball) prior to AP₁. In the single- and dual fusion-sensor models all release sites are occupied. In the unpriming model priming is in an equilibrium with unpriming and some release sites are empty. The dashed white graphs show the peak Ca²⁺ concentration (simulation of optimal fits for each model) during the first transient as a function of distance to the Ca²⁺ source. Second row: Some of the SVs fuse in response to AP₁. The dashed blue graphs show the pV_r1 as a function of distance. The large blue circles indicate pV_r1 = 0.25. In the unpriming model the larger Ca²⁺ influx (according to the optimal fit) increases the area from which SVs fuse. Third row: Right before AP₂ some of the empty release sites have been repopulated or newly filled by priming (orange balls). The shift in the (un)priming equilibrium in the unpriming model makes the increase in the number of primed SVs substantially larger than in the other models. The dashed white graphs show the peak Ca²⁺ concentration during the second transient as a function of distance to the Ca²⁺ source. Bottom row: SV fusion in response to AP₂. The large dashed red graphs show pV_r2 as a function of distance to the Ca²⁺ source. The blue and red circles indicate pV_r1 and pV_r2 of 0.25. In the dual fusion-sensor model, the second sensor increases pV_r between stimuli, but the effect is small, even in the best fit of the model. These cartoons illustrate the mechanisms underlying our fitting results of the different models: The dual fusion-sensor model shows a small increase in second release compared to the single-sensor model, but only the unpriming model reproduces the experimentally observed facilitation. Parameters used for simulations can be found in Tables 1–3.

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Tables

Table 1

Parameters of Ca²⁺ and buffer dynamics.

Simulation volume
r	Radius of cylindric simulation volume	623.99 nm
h	Height of cylindric simulation volume	1 µm
n_grid	Spatial grid points in CalC simulation	71 × 101 (radius x height)
Ca²⁺
Q_max	Scaling of the total amount of Ca²⁺ charge influx	Fitted (all models), see Table 2
D_Ca	Diffusion coefficient of Ca²⁺ (Allbritton et al., 1992)	0.223 µm²/ms
[Ca]_bgr	Background Ca²⁺	$\frac{[C a^{2 +}]_{e x t}}{[C a^{2 +}]_{e x t} + K_{M, c u r r e n t}} \cdot 190 nM$
K_M,current	Set to the same value as K_M,fluo determined in GCaMP6 experiments	2.679 mM
Ca²⁺ uptake	Volume-distributed uptake (Helmchen et al., 1997)	0.4 ms⁻¹
Buffer Bm (‘fixed’ buffer)
D_Bm	Diffusion coefficient	0.001 µm²/ms
K_D,Bm	Equilibrium dissociation constant (Xu et al., 1997)	100 µM
K_+,Bm	Ca²⁺ binding rate (Xu et al., 1997)	0.1 (µM⋅ms)⁻¹
K_-,Bm	Ca²⁺ unbinding rate: K_D,Bm⋅K_+,Bm	1 ms⁻¹
Total Bm	Total concentration (bound+unbound) (Xu et al., 1997)	4000 µM
Buffer ATP
D_ATP	Diffusion coefficient (Chen et al., 2015)	0.22 µm²/ms
K_D,ATP	Equilibrium dissociation constant (Chen et al., 2015)	200 µM
K_+,ATP	Ca²⁺ binding rate (Chen et al., 2015)	0.5 (µM⋅ms)⁻¹
K_-,ATP	Ca²⁺ unbinding rate: K_D,ATP⋅K_+,ATP	100 ms⁻¹
Total ATP	Total concentration (bound+unbound) (Chen et al., 2015)	650 µM
Resting Ca²⁺
K_M,current	Michaelis Menten-constant of resting Ca²⁺ (same as K_M,current of Ca²⁺ influx)	2.679 mM
[Ca²⁺]_max	Asymptotic max value of resting Ca²⁺	190 nM

Table 2

Best fit parameters of all models.

Models presented in main figures
	Single-sensor model (Figure 4)	Dual fusion-sensor model, cooperativity 2 (Figure 6)	Unpriming model, cooperativity 5 (Figure 7)
Q_max	8.42 fC	4.51 fC	13.77 fC
k_rep	165.53 s⁻¹	159.30 s⁻¹	134.85 s⁻¹
n_sites	216	211	180
k₂		4.10e7 M⁻¹s⁻¹
s		510.26
u			236.82 s⁻¹
k_M,prim			55.21 nM⁻¹
Cost value (see Materials and methods)	9.689	4.129	0.340
Models presented in figure supplements
	Dual fusion-sensor model, cooperativity 5 (Figure 6—figure supplement 1)	Unpriming model, cooperativity 2 (Figure 7—figure supplement 1)	Site activation model (Figure 7—figure supplement 3)
Q_max	8.10 fC	13.49 fC	12.59 fC
k_rep	492.56 s⁻¹	106.59 s⁻¹	141.20 s⁻¹
n_sites	112	203	189
k₂	5.41e6 M⁻¹s⁻¹
s	261.07
u		5207.70 s⁻¹
k_M,prim		7.61 nM⁻¹
β			0.09 s⁻¹
γ			194.77 s⁻¹
δ			10.70 s⁻¹
Cost value (see Materials and methods)	2.941	0.642	1.57

Table 3

Parameters of exocytosis simulation.

Parameter	Explanation and reference	Value
Common parameters
n_sites	Number of release sites (=maximal number of SVs)	Fitted (all models), see Table 2
L⁺	Basal fusion rate constant (Kochubey and Schneggenburger, 2011)	3.5⋅10⁻⁴ s⁻¹
q	Amplitude of the mEJC. Estimated from variance-mean of data (see Figure 2F)	0.6 nA
Fast sensor (all models)
n_max	Cooperativity, fast sensor (Lou et al., 2005; Schneggenburger and Neher, 2000; Wölfel et al., 2007)	5
k₁	Ca²⁺ binding rate, first sensor (Wölfel et al., 2007)	1.4⋅10⁸ M⁻¹s⁻¹
k_-1	Ca²⁺ unbinding rate, first sensor (Wölfel et al., 2007)	4000 s⁻¹
b_f	Cooperativity factor, first sensor (Lou et al., 2005; Wölfel et al., 2007)	0.5
k_f	Fusion rate constant of R(5,0) (fast sensor fully activated). (Lou et al., 2005; Schneggenburger and Neher, 2000; Wölfel et al., 2007)	6000 s⁻¹
f	${⟮ \frac{k_{f}}{L^{+}} ⟯}^{\frac{1}{5}}$	27.978
Replenishment (all models)
k_rep	Replenishment rate constant	Fitted (all models), see Table 2
Slow sensor (dual fusion-sensor model)
m_max	Cooperativity, second fusion sensor	2 (5 in figure supplement)
K_D	Dissociation constant, second fusion sensor (Brandt et al., 2012)	1.5 µM
k₂	Ca²⁺ binding rate, second fusion sensor	Fitted (dual fusion-sensor model), see Table 2
k_-2	Ca²⁺ unbinding rate, second fusion sensor	k_D⋅k₂
b_s	Cooperativity factor, second fusion sensor (=b_f)	0.5
s	Second fusion sensor analogue of f: factor on the fusion rate	Fitted (dual fusion-sensor model), see Table 2
Unpriming (unpriming model)
n	Cooperativity (exponent in unpriming rate equation)	5 (2 in figure supplement)
u	Rate constant of unpriming	Fitted (unpriming model), see Table 2
K_M,prim	Michaelis-Menten constant in expression of r	Fitted (unpriming model), see Table 2
Site activation (site activation model)
n	Cooperativity (exponent on [Ca²⁺]	5
α	Rate constant [I] to [D]	1e6 s^-1
β	Rate constant [D] to [I]	Fitted (site activation model), see Table 2
γ	Rate constant [D] to [A]	Fitted (site activation model), see Table 2
δ	Rate constant [A] to [D]	Fitted (site activation model), see Table 2

Key resources table

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Strain (Drosophila melanogaster)	w[1118]	BloomingtonDrosophilaStock Center
Genetic reagent (D. melanogaster)	Ok6-GAL4/II	(Aberle et al., 2002)	PMID:11856529	Ok6-Gal4/II crossed to w[1118]
Genetic reagent (D. melanogaster)	elav-Gal4/I	(Lin and Goodman, 1994)	PMID:7917288	Used for elav-GAL4/+;;UAS-Unc13A-GFP/+;P84200/P84200
Genetic reagent (D. melanogaster)	UAS-Unc13A-GFP/III	(Böhme et al., 2016)	PMID:27526206	Used for elav-GAL4/+;;UAS-Unc13A-GFP/+;P84200/P84200
Genetic reagent (D. melanogaster)	ry⁵⁰⁶; P{ry11}unc-13^P84200 / ci^D	Kyoto Stock Center	FlyBase: FBst0300878	Used for elav-GAL4/+;;UAS-Unc13A-GFP/+;P84200/P84200
Genetic reagent (D. melanogaster)	w[1118]; P{w[+mC]=Mhc-SynapGCaMP6f}3–5	(Newman et al., 2017) BloomingtonDrosophilaStock Center	PMID:28285823 Bloomington Stock # 67739
Genetic reagent (D. melanogaster)	w[1118]; P{y[+t7.7] w[+mC]=20XUAS-IVS-665GCaMP6m}attP40/Ok6-GAL4	BloomingtonDrosophilaStock Center	Bloomington Stock # 42748
Antibody	Anti-Unc13A (guinea pig polyclonal)	(Böhme et al., 2016)	PMID:27526206	Dilution: 1:500
Antibody	Anti guinea pig STAR635 (goat polyclonal)	(Böhme et al., 2016)	PMID:27526206	Dilution: 1:100
Antibody	Anti Nc82 (mouse monoclonal)	Developmental Studies Hybridoma Bank	Antibody Registry ID: AB_2314866	Dilution: 1:1000
Antibody	Anti-mouse Cy5 (goat polyclonal)	Jackson ImmunoResearch	SKU: 115-175-072	Dilution: 1:500
Software, algorithm	LAS X software	Leica Microsystems	https://www.leica-microsystems.com
Software, algorithm	LCS AF	Leica Microsystems	Leica Microsystems
Software, algorithm	Image J	NIH	Version 1.48q/1.50 g; https://imagej.nih.gov/ij/
Software, algorithm	Imspector Software	Max Planck Innovation	Version 0.10
Software, algorithm	MATLAB	MathWorks	R2010b/R2016b
Software, algorithm	Clampfit	Molecular Devices	Version 10.3
Software, algorithm	GraphPad Prism	GraphPad Software	Version 5.01/6.01
Software, algorithm	pClamp 10	Molecular Devices
Software, algorithm	CalC	(Matveev et al., 2002)	PMID:12202362 Version 6.8.6
Other	Computer grid	Bioinformatics Center, University of Copenhagen	https://www1.bio.ku.dk/scarb/bioinformatics-centre/	Used for simulations
Other	custom-built STED-microscope	(Göttfert et al., 2017)	PMID:23823248
Other	HPF machine (HPM100)	Leica Microsystems	https://www.leica-microsystems.com
Other	AFS	Leica Microsystems	https://www.leica-microsystems.com
Other	Ultramicrotome (RMC PowerTome XL; Reichert Ultracut S)	Leica Microsystems	https://www.leica-microsystems.com
Other	Electrone microscope (TecnaiSpirit; FEI or Zeiss 900)	FEI; Zeiss	https://www.fei.com,https://www.zeiss.com

Author response table 1

	95% CI, lower bound	Best fit	95% CI, higher bound
Parameter value (σ)	62.53 nm	76.52 nm	98.61 nm
Mean of Rayleigh	78.37 nm	95.90 nm	123.59 nm
SD of Rayleigh	40.97 nm	50.13 nm	64.60 nm
Mean of integrated Rayl	99.76 nm	122.08 nm	157.36 nm
SD of integrated Rayl	42.12 nm	51.52 nm	66.40 nm

Author response table 2

	95% CI, lower bound	Estimated mean/SD of distribution	95% CI, higher bound
Mean of Rayleigh	78.37 nm (CI from likelihood)	95.90 nm	123.59 nm (CI from likelihood)
SD of Rayleigh	40.97 nm (CI from likelihood)	50.13 nm	64.60 nm (CI from likelihood)
Mean from bootstrap	72.74 nm (CI from quantiles)	94.85 nm	118.32 nm (CI from quantiles)
SD from bootstrap	37.37 nm (CI from quantiles)	51.52 nm	65.21 nm (CI from quantiles)

Additional files

Source code 1 MATLAB scripts used for simulations.: https://cdn.elifesciences.org/articles/51032/elife-51032-code1-v2.zip
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Transparent reporting form: https://cdn.elifesciences.org/articles/51032/elife-51032-transrepform-v2.docx
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Janus RL Kobbersmed
Andreas T Grasskamp
Meida Jusyte
Mathias A Böhme
Susanne Ditlevsen
Jakob Balslev Sørensen
Alexander M Walter

(2020)

Rapid regulation of vesicle priming explains synaptic facilitation despite heterogeneous vesicle:Ca²⁺ channel distances

eLife 9:e51032.

https://doi.org/10.7554/eLife.51032

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Deriving the spatial docked SV distribution.

Figure 1—source data 1

Figure 1—source data 2

EM + STED vesicle positions are consistent between independent datasets and overlapping with each other.

Characterization of short-term plasticity at the Drosophila melanogaster NMJ.

Figure 2—source data 1

Figure 2—source data 2

Figure 2—source data 3

Illustration of analysis of experimental electophysiological data.

Figure 2—figure supplement 1—source data 1

Illustration of fluctuation analysis (quantification across cells shown in Figure 2F) in a single representative cell.

Electrophysiological comparison of synaptic transmission in wildtype (w[1118], +/+) (black) and Ok6-Gal4/+ (orange) flies.

Figure 2—figure supplement 3—source data 1

Simulation of AP-induced synaptic Ca2+ profiles.

Figure 3—source data 1

Experiment to determine the dependence of AP-induced Ca2+ influx on the extracellular Ca2+ concentration.

Ca2+ profiles of all models using best fit parameters (reported in Table 1; Table 2).

A single-sensor model reproduces the magnitude of transmission to single APs, but cannot account for STF and variances.

Figure 4—source data 1

Stochastic and deterministic simulations yield different PPR values.

Analysis of the spatial dependence of SV fusion in the single-sensor model reveals a near-identical use of release sites during the two APs, thereby favoring STD.

A dual fusion-sensor model of Ca2+ sensors cooperating for SV fusion improves STP behavior, but suffers from too little STF, asynchronous release and too much variance.

Figure 6—source data 1

The dual fusion-sensor sensor model with cooperativity 5 (allowing the binding of 5 Ca2+ to the second fusion sensor).

An unpriming model with Ca2+ dependent regulation of the RRP accounts for experimentally observed Ca2+ dependent eEJCs, STP and variances.

Figure 7—source data 1

The unpriming model with cooperativity 2.

A model with Ca2+-dependent release site activation accounts for experimentally observed eEJCs, STP and variances.

Simulation based time course predictions of paired-pulse STF recovery for different interstimulus intervals across different Ca2+ concentrations (0.75–10 mM).

The unpriming model counteracts short-term depression by increasing the number of responsive SVs between stimuli and predicts a more efficient use of SVs throughout the synapse.

Cartoon illustrations of the single-sensor, the dual fusion-sensor, and the unpriming models during a paired-pulse simulation at 0.75 mM extracellular Ca2+.

The histogram in Author response image 2 shows the sampled mean with 95 % confidence interval marked.

Parameters of Ca2+ and buffer dynamics.

Best fit parameters of all models.

Parameters of exocytosis simulation.

Source code 1

Transparent reporting form

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Simulation of AP-induced synaptic Ca²⁺ profiles.

Experiment to determine the dependence of AP-induced Ca²⁺ influx on the extracellular Ca²⁺ concentration.

Ca²⁺ profiles of all models using best fit parameters (reported in Table 1; Table 2).

A dual fusion-sensor model of Ca²⁺ sensors cooperating for SV fusion improves STP behavior, but suffers from too little STF, asynchronous release and too much variance.

The dual fusion-sensor sensor model with cooperativity 5 (allowing the binding of 5 Ca²⁺ to the second fusion sensor).

An unpriming model with Ca²⁺ dependent regulation of the RRP accounts for experimentally observed Ca²⁺ dependent eEJCs, STP and variances.

Cartoon illustrations of the single-sensor, the dual fusion-sensor, and the unpriming models during a paired-pulse simulation at 0.75 mM extracellular Ca²⁺.

Parameters of Ca²⁺ and buffer dynamics.