1. Neuroscience

RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses

  1. Marisa M Brockmann
  2. Marta Maglione
  3. Claudia G Willmes
  4. Alexander Stumpf
  5. Boris A Bouazza
  6. Laura M Velasquez
  7. M Katharina Grauel
  8. Prateep Beed
  9. Martin Lehmann
  10. Niclas Gimber
  11. Jan Schmoranzer
  12. Stephan J Sigrist  Is a corresponding author
  13. Christian Rosenmund  Is a corresponding author
  14. Dietmar Schmitz  Is a corresponding author
  1. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany
  2. Institut für Biologie, Germany
  3. Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Germany
  4. NeuroCure Cluster of Excellence, Germany
  5. German Center for Neurodegenerative Diseases, Germany
https://doi.org/10.7554/eLife.43243
Share this article
Cite this article
  1. Marisa M Brockmann
  2. Marta Maglione
  3. Claudia G Willmes
  4. Alexander Stumpf
  5. Boris A Bouazza
  6. Laura M Velasquez
  7. M Katharina Grauel
  8. Prateep Beed
  9. Martin Lehmann
  10. Niclas Gimber
  11. Jan Schmoranzer
  12. Stephan J Sigrist
  13. Christian Rosenmund
  14. Dietmar Schmitz
(2019)
RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses
eLife 8:e43243.
https://doi.org/10.7554/eLife.43243
  2. Download BibTeX
  3. Download .RIS

Abstract

All synapses require fusion-competent vesicles and coordinated Ca2+-secretion coupling for neurotransmission, yet functional and anatomical properties are diverse across different synapse types. We show that the presynaptic protein RIM-BP2 has diversified functions in neurotransmitter release at different central murine synapses and thus contributes to synaptic diversity. At hippocampal pyramidal CA3-CA1 synapses, RIM-BP2 loss has a mild effect on neurotransmitter release, by only regulating Ca2+-secretion coupling. However, at hippocampal mossy fiber synapses, RIM-BP2 has a substantial impact on neurotransmitter release by promoting vesicle docking/priming and vesicular release probability via stabilization of Munc13-1 at the active zone. We suggest that differences in the active zone organization may dictate the role a protein plays in synaptic transmission and that differences in active zone architecture is a major determinant factor in the functional diversity of synapses.

https://doi.org/10.7554/eLife.43243.001

Introduction

Across all types of synapses, vesicle fusion is coordinated by an evolutionarily conserved set of vesicular and active zone proteins (Südhof, 2012). One hallmark of synapses is their functional heterogeneity: indeed, synapses can exhibit high or low transmission fidelity, and this diversity results in synapse-specific differences in response fluctuation and short-term plasticity (Atwood and Karunanithi, 2002; O'Rourke et al., 2012). In recent years, functional synaptic diversity has been found to be critical for routing and encoding sensory information within networks of neurons in the brain (Chabrol et al., 2015). Functional synaptic diversity has been observed both within and across brain regions, and it has been shown to play a significant role in temporal coding of multisensory integration and extraction of specific sensory features (Atwood and Karunanithi, 2002; O'Rourke et al., 2012; Chabrol et al., 2015). Still, the molecular origin of this heterogeneity is largely unknown, and analyses of genotype-phenotype differences across species and brain tissue have just started to uncover key molecular principles responsible for synaptic diversity, emphasizing the importance of abundance and isoforms differences across species for synaptic diversity (Rosenmund et al., 2002; Weston et al., 2011; Hu et al., 2013; Böhme et al., 2016).

It is possible, but largely untested whether the active zone architecture, which is specialized throughout synapse types, is associated with distinct protein functions and thus contributes to synaptic diversity. Here, RIM-binding proteins (RIM-BPs) are particularly interesting, as their loss manifests in severe phenotypes in the Drosophila neuromuscular junction (NMJ) (Liu et al., 2011), but rather subtle phenotypes in small central murine synapses, the Calyx of Held or the ribbon synapse with only mild impairments in Ca2+-channel-release site coupling (Acuna et al., 2015; Grauel et al., 2016; Luo et al., 2017; Davydova et al., 2014). Drosophila NMJ and small central synapses are considerable distinct in their anatomical, ultrastructural and, physiological properties (Ackermann et al., 2015).

To understand whether the RIM-BP2 phenotypes described so far are species or synapse type dependent, we chose to examine RIM-BP2 function at mouse hippocampal mossy fiber (MF) synapses, a mammalian synapse with distinct physiologically and anatomically properties. Notably, MF synapses strongly facilitate and possess multiple release sites (Nicoll and Schmitz, 2005).

Together, our laboratories previously published a detailed analysis on RIM-BP2 function at Schaffer collateral (SC; CA3-CA1) synapses using murine hippocampal autaptic neurons and acute brain slices (Grauel et al., 2016). Combining electrophysiological recordings and gSTED analysis, we concluded that RIM-BP2 mildly affects neurotransmissions by altering Ca2+-channel-release site coupling and affecting synaptic release probability at these synapses.

Now, extended analysis of how RIM-BP2 impacts on synaptic integrity revealed that neurotransmission at MF synapses is severely impaired upon the loss of RIM-BP2, compared to that at SC synapses. Furthermore, we also show that RIM-BP2 loss leads to a defective stabilization of Munc13-1 clusters at the active zone specifically at MF synapses, but not at SC synapses, indicative of diversified functions of RIM-BP2 at these two synapse types. While at SC synapses RIM-BP2 maintains high fidelity coupling of Ca2+-channels to release sites, at MF synapses RIM-BP2 is required to stabilize Munc13-1 clusters to ensure vesicle docking/priming. In addition, RIM-BP2 deletion alters vesicular release probability at MF terminals most probably via increased distances between Ca2+-channels and release sites mapped by Munc13-1. Finally, our analysis of the active zone architecture revealed that RIM-BP2 and Munc13-1 clusters as well as RIM1 and Cav2.1 clusters are positioned at increased distances in MF synapses compared to that in CA3-CA1 synapses, demonstrating that these synapses utilize different architectural organizational principles.

Results

Distinct role of RIM-BP2 at hippocampal synapses

To probe the nature of diversity between central mammalian synapses, we examined the role of RIM-BP2 throughout the hippocampus. Immunostainings for RIM-BP2 in mouse hippocampal slices revealed RIM-BP2 expression in the whole hippocampal neuropil, with a strong labeling of the mossy-fiber layer band in the CA3 stratum lucidum (Figure 1a).

Figure 1
Download asset Open asset
RIM-BP2 KO affects synaptic transmission specifically at MF synapses.

(a) Immunostaining of RIM-PB2 in hippocampal brain slices (DG = dentate gyrus) and schematic illustration of recording configurations. (b) Input-output of synaptic transmission, plotted as PFV against fEPSP amplitude, of associative commissural (AC) and Schaffer collateral (SC) synapses showed no difference between RIM-BP2 WT and KO slices (AC: n(WT)=17 slices/6 animals; n(KO)=21 slices/6 animals) (SC: n(WT)=9 slices/3 animals; n(KO)=12 slices/3 animals). Sample traces show averages of 10 sweeps. Values represent mean ± SEM. (c) Input-output of synaptic transmission of MF synapses, plotted as PFV against fEPSP amplitude (MF: n(WT)=22 slices/7 animals; n(KO)=18 slices/7 animals). Sample traces show averages of 10 sweeps. (d) Frequency facilitation with 1 Hz stimulation of MF synapses (sweep 10–30). Sample traces show averages of five sweeps before (gray) and at the end of 1 Hz stimulation (black). For statistics please see Figure 1—source data 1.

https://doi.org/10.7554/eLife.43243.002
Figure 1—source data 1

Statistics of data presented in Figure 1.

https://doi.org/10.7554/eLife.43243.003

To analyze the functional impact of RIM-BP2 loss at different hippocampal synapses, we recorded field excitatory postsynaptic potentials (fEPSPs) in acute brain slices obtained from RIM-BP2 KO mice and wildtype (WT) littermates. Synaptic transmission was assessed at three different hippocampal synapses: the Mossy fiber – pyramidal cell synapse (MF-CA3), the Associational – commissural synapses (AC-CA3), and the SC synapse (CA3-CA1) (illustrated in Figure 1a). To ensure MF origin, we verified input sensitivity to group II metabotropic glutamate receptor (mGluR) agonist DCG IV (Yoshino et al., 1996). The ratio of fEPSP to presynaptic fiber volley (PFV) was drastically reduced when stimulating the MF pathway in RIM-BP2 deficient (KO) slices compared to that in WT slices (Figure 1c). This shows that neurotransmission is severely impaired upon loss of RIM-BP2 at MF synapses. In contrast, the ratio of fEPSP to presynaptic fiber volley (PFV) for associative commissural (AC)-fibers and Schaffer collaterals (SC), both representing small central synapses, were not affected by the loss of RIM-BP2 (Figure 1b). Thus, RIM-BP2 deletion specifically impairs neurotransmitter release at hippocampal MF synapses, compared to AC and SC synapses.

To further characterize the defect in neurotransmission at MF synapses upon loss of RIM-BP2, we analyzed frequency facilitation at MF synapses by applying a stimulus train of 1 Hz. Normalized fEPSPs amplitudes were significantly increased in RIM-BP2 deficient synapses at the end of 1 Hz train stimulation, suggesting a role of RIM-BP2 in short-term plasticity at the MF synapse (Figure 1d).

In addition, we recorded in whole cell patch-clamp mode from CA3-pyramidal neurons in acute hippocampal slices and stimulated MF EPSCs. However, it was extremely difficult to find a quantifiable input of mossy fibers onto CA3 pyramids in the RIM-BP2 KOs, which was in sharp contrast to responses from WT animals. This strong phenotype made a comparative analysis of synaptic properties using whole cell recordings unfeasible.

RIM-BP2 deletion does not alter Ca2+-channel localization at the MF synapse

Given that RIM-BP2 contributes to high fidelity coupling of Ca2+-channels and release apparatus in CA3-CA1 synapses (Acuna et al., 2015; Grauel et al., 2016), the disruption in synaptic transmission in the MF synapse may also arise from alterations in active zone organization.

Since MF terminals are unique in their morphology, we first assessed the active zone molecular architecture from WT mice. Therefore, we used triple-channel gSTED, with a lateral resolution of approximately 50 nm in all channels (Grauel et al., 2016). Due to limited capacity of antibodies combination, we could not combine specific markers to differentiate between MF postsynaptic partners in our immunostainings. We thereby refer to MF terminals or synapses in our analysis. In order to define putative differences in the active zone architecture at MF and CA3-CA1 synapses, we utilized super-resolution STED-microscopy based on detection of major active zone proteins intensities, here referred to as protein clusters. Quantification of the localization of these protein clusters was mainly performed by counting and measuring distances between intensities of these marker proteins. We compared the distribution of RIM-BP2 to the active zone markers Munc13-1 and Bassoon as a proxy for active zone organization. Protein clusters were determined by peak intensities, after image thresholding and watershed segmentation. We analyzed the k nearest neighbor distances (dk) between clusters formed by these proteins by measuring Euclidean distances between the centers of each cluster, using a semi-automated analysis described previously (Grauel et al., 2016) (Figure 2a–c). Since the k nearest neighbor distance analysis was performed in parallel on the same processed brain slice preparations as our previously published gSTED experiments at CA3-CA1 synapses, we were able to compare protein cluster distances between both synapse types. The average distance of the closest RIM-BP2 cluster relative to a given Bassoon cluster at MF synapses was comparable to CA3-CA1 synapses. However, the closest Munc13-1 cluster in the MF synapse was 51% further away from a RIM-BP2 cluster (174 ± 20 nm, Figure 2c) than what we previously observed at CA3-CA1 synapses (115 ± 5 nm) (Grauel et al., 2016). Our gSTED analysis does not allow the differentiation between intra- and inter- active zone protein clusters. However, ultrastructural quantifications of the MF active zone size (0.12 µm2) (Rollenhagen et al., 2007), are consistent with four RIM-BP2, two Bassoon, and three Munc13-1 clusters per active zone (Figure 2c). Regardless of this semiquantitative analysis, the difference in Munc13-1/RBP cluster distances is indicative for distinct active zone organization between MF and CA3-CA1 synapses.

Figure 2 with 1 supplement see all
Download asset Open asset
RIM-BP2 deletion does not alter the localization of CaV2.1 clusters relative to the active zone protein RIM1 and the postsynaptic marker Homer1 at MF synapses.

(a) Confocal (left) and gSTED (right) images of RIM-BP2, Munc13-1 and Bassoon (Bsn) at the active zone (AZ) of WT MF boutons (MFBs) in situ. Arrows indicate synapses in side view. (b) Example of k nearest neighbor distance analysis of protein clusters at MF synapses. Following image thresholding and Watershed segmentation, X and Y coordinates of each segmented cluster identified were retrieved and Euclidean distances of for example Munc13-1 clusters relative to a given RIM-BP2 cluster calculated with a custom-written MATLAB script. Several hundreds to thousands of clusters per image were analyzed and values averaged per animal (n = 6). (c) Upper, mean k nearest neighbor distances for Munc13-1 clusters relative to a given RIM-BP2 (left) or Bassoon (middle) cluster and for RIM-BP2 clusters relative to a given Bassoon cluster (right). Lower, mean k nearest neighbor distances for Munc13-1 clusters relative to Munc13-1 itself as center (left), for Bassoon clusters relative to itself (middle) and RIM-BP2 clusters relative to itself (right). Based on ultrastructural studies of MF AZ size, estimating an AZ diameter of 391 nm, at WT MFBs we detected at least three Munc13-1 clusters, two Bassoon clusters and four RIM-BP2 clusters within a single AZ, having a dk <391 nm.(d) gSTED images of CaV2.1, RIM1 and Homer1 clusters at MFBs of RIM-BP2 WT and KO brain slices. Arrows indicate synapses with two Cav2.1 clusters apposed to a single Homer1 cluster. (e) Average number of Cav2.1, RIM1 and Homer1 clusters found at MFBs and cluster ratio per each RIM-BP2 WT (n = 9) and KO (n = 9) mouse analyzed (f). No significant differences were observed between the two groups. (g) Example of k nearest neighbor distance analysis of protein clusters at MF synapses. Several hundreds to thousands of clusters per image were analyzed and values averaged per animal. (h) k nearest neighbor distances of the first and second closest RIM1 k neighbor (k = 1, k = 2) relative to a given Cav2.1 (first left), no significant differences were observed between RIM-BP2 WT and KO mice. No significant differences were observed also for the mean k nearest neighbor distance at which Cav2.1 clusters are located relative to a given Cav2.1 (second left). Based on ultrastructural studies of MF AZ size, estimating an AZ diameter of 391 nm, at WT MFBs we detected one RIM1 cluster and three Cav2.1 clusters per single active zone, having a dk <391 nm. No significant difference was observed for Cav2.1 and RIM1 localization in relation to Homer1 (third left and first right, respectively). Values represent mean ± SEM. For statistics please see Figure 2—source data 1.

https://doi.org/10.7554/eLife.43243.004
Figure 2—source data 1

Statistics of data presented in Figure 2.

https://doi.org/10.7554/eLife.43243.007

We next asked whether changes in protein cluster distribution might account for the impaired release in RIM-BP2 deficient MF synapses. First, in accordance to the phenotype observed at the CA3-CA1 synapse (11,12d), we determined the position of clusters formed by the P/Q type Ca2+-channel subunit Cav2.1 in relation to clusters formed by the active zone protein RIM1, and the postsynaptic scaffold Homer1 in RIM-BP2 WT and KO MF synapses. Surprisingly, neither the number, the ratio of protein clusters nor the distance of RIM1 or Homer1 clusters to a given Cav2.1 cluster were altered upon the loss of RIM-BP2 (Figure 2d–f). As for RIM-BP2, Munc13-1, and Bassoon we computed the putative number of clusters formed by Cav2.1 and RIM1 that would fit in an average MF active zone (Figure 2g). According to the threshold applied, we detected in average three Cav2.1 clusters and one RIM1 clusters per single active zone in WT mice (Figure 2h). We further analyzed the cluster number and k nearest neighbor distances of RIM1, as main interacting scaffold protein of RIM-BP2. The cluster number of RIM1 as well as the nearest neighbor distance between Homer1 and RIM1 clusters was unaltered in RIM-BP2 deficient MF synapses (Figure 2g,h). Although we observed a higher variability in the RIM1/Cav2.1 cluster ratio in RIM-BP2 KO mice (Figure 2e,f), our data suggest that the loss of RIM-BP2 does not grossly alter RIM1 cluster number or localization at MF terminals.

To probe again for differential organizations of MF and CA3-CA1 synapses, we compared in simultaneously acquired images from the same brain slices (Grauel et al., 2016), the distance between RIM1 and Cav2.1 clusters in both synapses. Interestingly, we found a 35% larger distance between RIM1 and Cav2.1 in MF synapses, again suggesting a differential nanoarchitecture of MF active zones.

Our unbiased k nearest neighbor analysis measures the distance of thousands of neighboring protein clusters found in one image. However, it does not allow us to discriminate protein clusters within or between nearby active zones unequivocally. To retrieve a more direct determination of distances within the active zone, we performed line profile measurements of peak-to-peak distances between protein clusters in selected active zones that are defined to be opposite to the postsynaptic marker Homer1. We analyzed only well-defined synapses in side or planar view. As shown with our k nearest neighbor analysis, line profile measurements did not reveal a significant change in the distance between two adjacent Cav2.1 clusters comparing RIM-BP2 WT and KO MF synapses (Figure 2—figure supplement 1), indicative of unaltered P/Q type Ca2+-channel localization within a given MF active zone upon loss of RIM-BP2. Our line profile measurements retrieved a distance between two Cav2.1 clusters of 184 ± 6 nm, a distance shorter than the one obtained with our semi-automated analysis (238 ± 23 nm), possibly indicating a subpopulation of synapses selected or mapping of clusters belonging to neighboring active zones, respectively.

RIM-BP2 stabilizes Munc13-1 protein clusters at MF synapses

We next compared the relative localization and abundance of Munc13-1 clusters and their distance to Ca2+-channels in RIM-BP2 WT and KO brain slices. In these experiments we identified MF synapses by their expression of the vesicular ZnT3, enriched at these synapses (Wenzel et al., 1997). Interestingly, we found a drastic reduction in the number of Munc13-1 clusters in RIM-BP2 deficient synapses, accompanied by a decrease in Munc13-1 clusters at specific distances from a given Cav2.1 clusters (Figure 3a–e). Therefore, in RIM-BP2 deficient MF active zones we detect less Munc13-1 clusters, which also were located at an increased distance to Cav2.1 clusters compared to WT MF synapses (Figure 3f,g). In contrast, the Munc13-1 cluster number and distribution at CA3-CA1 synapses were unaltered upon RIM-BP2 loss (Figure 3h–m), indicating that the observed reduction in the Munc13-1 cluster number is specific for MF synapses. To ensure the analysis of intra-active zone clusters, we performed line profile measurements assessing the peak intensity distance between Munc13-1 and Cav2.1 clusters in RIM-BP2 WT and KO MF synapses. Peak-to-peak distance measurements revealed a significantly increased distance of Munc13-1 clusters relative to Cav2.1 clusters in RIM-BP2 deficient MF synapses compared to WT (Figure 3—figure supplement 1), supporting our results from the semi-automated k nearest neighbor analysis.

Figure 3 with 4 supplements see all
Download asset Open asset
Loss of RIM-BP2 specifically reduces Munc13-1 levels at MF synapses but not at CA3-CA1 synapses.

(a) Representative gSTED images of CaV2.1 and Munc13-1 clusters at MF boutons (MFB) identified by ZnT3 expression (confocal) in RIM-BP2 WT and KO brain sections. Arrows indicate Munc13-1 clusters nearby CaV2.1 clusters. (b) Example of k nearest neighbor distance analysis of Munc13-1 clusters relative to a given Cav2.1 cluster at MF synapses. Following image thresholding and Watershed segmentation, X and Y coordinates of each segmented cluster identified were retrieved and Euclidean distances of for example Munc13-1 clusters relative to a given Cav2.1 cluster calculated with a custom-written MATLAB script (b, upper). Similarly, we retrieved the number of for example Munc13-1 clusters found at specific distance intervals (nm) from a given Cav2.1 cluster (b, lower). Several hundreds to thousands of clusters per image were analyzed and values averaged per animal. (c) Average number of Cav2.1 clusters within the ZnT3 +area found per each RIM-BP2 WT (n = 8) and KO (n = 6) animal analyzed. ZnT3 was used as marker to identify MF synapses. (d) Average number of Munc13-1 clusters within the ZnT3 +area found per each RIM-BP2 WT and KO animal analyzed (e) Ratio of Munc13-1 clusters/Cav2.1 clusters in RIM-BP2 KO and WT mice. (f) The number of Munc13-1 clusters at determined distance intervals (nm) from a given Cav2.1 cluster decreased significantly at all distances analyzed in RIM-BP2 KO, while the distance of the first closest k neighbor (k = 1; g) up to the fourth (k = 4) significantly increased. (h) Representative gSTED images of Cav2.1 and Munc13-1 clusters at CA3-CA1 synapses in RIM-BP2 WT and KO brain sections. Arrows indicate Munc13-1 clusters adjacent to Cav2.1 clusters. (i) Average number of Cav2.1 clusters and Munc13-1 clusters (j) found within the field of view at CA3-CA1 synapses in RIM-BP2 KO (n = 6) and WT (n = 9) mice (k) Ratio of Munc13-1 clusters/Cav2.1 clusters at CA3-CA1 synapses. (l) At CA3-CA1 synapses, loss of RIM-BP2 does not significantly alter either the number of Munc13-1 clusters at determined distance intervals (nm) from a given Cav2.1 cluster or the distance at which the first closest k neighbor (k = 1, (m) is found. Values represent mean ± SEM. *p<0.05, **p<0.01. For statistics please see Figure 3—source data 1.

https://doi.org/10.7554/eLife.43243.008
Figure 3—source data 1

Statistics of data presented in Figure 3.

https://doi.org/10.7554/eLife.43243.017

To further validate our results on Munc13-1 localization within a single active zone, we analyzed by line profile measurements inter-cluster distances of two Munc13-1 clusters opposed to Homer1 at MF and CA3-CA1 terminals of RIM-BP2 WT and KO mice. Confirming our nearest neighbor analysis, the peak-to-peak distance between two Munc13-1 clusters increased at RIM-BP2 KO MF active zones, in contrast to CA3-CA1 synapses (Figure 3—figure supplement 2). Notably, as shown for Cav2.1 inter-cluster measurements, the distances between Munc13-1 and Cav2.1 clusters or inter-Munc13-1 clusters retrieved by line profile measurements were shorter than the one retrieved with our semi-automated analysis, possibly indicating a subpopulation of synapses selected or mapping of clusters belonging to neighboring active zones, respectively.

Altogether, our gSTED analysis demonstrates that RIM-BP2 is essential in stabilizing Munc13-1 protein clusters specifically at MF synapses.

To analyze if the loss of RIM-BP2 synapse specifically affects protein clustering or total protein amount, we examined protein levels of Munc13-1 at SC and MF synapses. Munc13-1 intensity levels were quantified on confocal images acquired in parallel to corresponding gSTED images. Deletion of RIM-BP2 resulted in a significant reduction of Munc13-1 intensity levels at MF synapses but not at CA3-CA1 terminals (Figure 3—figure supplement 3).

We also analyzed the relative distribution and abundance of Munc13-2 clusters relative to a given Cav2.1 cluster at both MF and CA3-CA1 synapses. In both synapses, loss of RIM-BP2 neither altered the number of protein clusters nor the distribution of Munc13-2 clusters relative to Cav2.1 channels (Figure 3—figure supplement 4), showing that the observed electrophysiological phenotype is not due to Munc13-2 loss (Breustedt et al., 2010).

RIM-BP2 docks synaptic vesicles via the specific recruitment of Munc13-1 at MF synapses

The primary role of Munc13-1 is to dock and prime synaptic vesicles (SV) at the active zone (Imig et al., 2014; Augustin et al., 1999). To explore whether the reduction in Munc13-1 clusters at RIM-BP2 deficient MF synapse might result in a decrease of vesicle docking, we analyzed their ultrastructural anatomy by electron microscopy (Figure 4a). We made use of high-pressure freezing fixation followed by freeze substitution, since conventional chemical fixation cannot reveal the Munc13-1 dependent loss in SV docking (Varoqueaux et al., 2002; Camacho et al., 2017). High-pressure freezing of acute hippocampal slices (4–6 weeks) show a ~ 25% reduction in docked SVs in RIM-BP2 deficient MF synapses compared to WT MF synapses (Figure 4c). The size of the post-synaptic density (PSD) was unaltered upon the loss of RIM-BP2 indicating that RIM-BP2 does not affect trans-synaptic interactions at MF synapses (Figure 4b). To evaluate whether the deletion of RIM-BP2 in acute hippocampal slices also affects SV docking at SC synapses we analyzed SV distribution at small central synapses in the CA1 area in parallel. However as expected from previous results in culture (Grauel et al., 2016), the number of docked SVs in CA1 synapses was unaltered in RIM-BP2 deficient synapses compared to synapses from WT slices (Figure 4b,f).

Figure 4
Download asset Open asset
Loss of RIM-BP2 specifically affects vesicle docking at MF synapses.

Representative EM images of MF synapses from acute hippocampal slices obtained from RIM-BP2 KO (black: three animals/each2-3 slices/78 active zones) and WT (red: three animals/2–3 slices each/52 active zones) mice. (b) Representative EM images of CA1 synapses from acute hippocampal slices obtained from RIM-PB2 KO (black: three animals/each2slices/27 active zones) and WT (red: three animals/2 slices each/25 active zones) mice. (c) Frequency distribution and bar graph show no difference in the size in the post-synaptic density (PSD) in MF active zones from WT or RIM-BP2 KO slices. (d) Frequency distribution and bar graph show a reduction of docked vesicles per 100 nm of the active zone at RIM-BP2 KO MF synapse compared to WT MF synapses. (e) Frequency distribution and bar graph depict no difference in the number of docked large vesicles (LV) (vesicle diameter >70 nm) (f) Frequency distribution and bar graph of docked vesicles at CA3-CA1 synapses show no difference between WT and RIM-BP2 KO. Values represent mean ± SEM. *p<0.05, **p<0.01, ***p<0.001. For statistics please see Figure 4—source data 1.

https://doi.org/10.7554/eLife.43243.018
Figure 4—source data 1

Statistics of data presented in Figure 4.

https://doi.org/10.7554/eLife.43243.019

MF synapses also contain a small but distinct fraction of large clear vesicles (>70 nm diameter; Henze et al., 2002; Rollenhagen and Lübke, 2010), which generate mEPSC >100 pA upon fusion (Henze et al., 2002). The number of large docked vesicles per active zone was however not affected by the deletion of RIM-BP2 (Figure 4e).

Thus, in contrast to CA3-CA1 synapses, MF synapses require RIM-BP2 dependent stabilization of Munc13-1 at the active zone to dock synaptic vesicles.

Loss of RIM-BP2 impairs vesicle priming and release efficiency in granule autaptic neurons

To examine the functional impact of RIM-BP2 loss in MF synapses, we prepared autaptic cultures of hippocampal granule cells that form synaptic contacts only with themselves and therefore allow the quantitative analysis of synaptic input-output properties. It is important to note that cultured granule cells form MF like boutons as assessed by EM analysis (Figure 5—figure supplement 1) and are sensitive to the application of DCG IV (Figure 5a,b and Figure 5—figure supplement 1). Therefore, granule autaptic neurons exhibit key aspects of hippocampal granule cell identity. Interestingly, since autapses just form synapses with themselves, their specialized protein expression and presynaptic ultrastructure are likely to be intrinsically encoded and mostly independent of the postsynaptic target.

Figure 5 with 2 supplements see all
Download asset Open asset
RIM-BP2 KO affects synaptic transmission at granule autaptic neurons.

(a) Sample traces of evoked EPSC amplitudes before (black) and after DCG IV application (gray) for RIM-BP2 WT and KO neurons. RIM-BP2 KO neurons were rescued by lentiviral transduction of RIM-BP2. (Number of experiments (cells/cultures); EPSC WT (70/4); KO (78/4); RIM-BP2 (24/3)) (b) Summary graphs of normalized EPSC amplitudes evoked by 2 ms depolarization (red arrow). (c) Sample traces and (d) summary graphs of normalized RRP responses elicited by a 5 s application of 500 mM sucrose. Summary graph of the PVR calculated as the ratio of the EPSC charge and the RRP charge. (Sucrose WT (69/4); KO (59/4); RIM-BP2 (24/3)) .(e) Sample traces of evoked EPSC amplitudes with an interstimulus interval of 25 ms. (f) Summary graph of paired-pulse ratio (PPR) of RIM-BP2 WT, KO and RIM-BP2 rescued autaptic granule neurons. (PPR WT (70/4); KO (74/4); RIM-BP2 (24/3)) (g) Summary graph of Paired-Pulse-Ratio (PPR) of granule cells with different inter-stimulus intervals of RIM-BP2 WT and KO granule autapses (PPR WT (28/2), PPR KO (29/2)). (h) Sample traces of miniature EPSCs (mEPSCs) and summary graph of mEPSC frequencies. (mEPSC WT (63/4); KO (43/4); RIM-BP2 (24/3)). Values represent mean ± SEM. *p<0.05, **p<0.01, ***p<0.001. For statistics please see Figure 5—source data 1.

https://doi.org/10.7554/eLife.43243.020
Figure 5—source data 1

Statistics of data presented in Figure 5.

https://doi.org/10.7554/eLife.43243.024

We first tested whether autaptic granule neurons also show a reduction in neurotransmitter release upon RIM-BP2 loss and thus whether they can be used as a model system to study synapse diversity. Consistent with the findings from hippocampal field recordings (Figure 1), evoked excitatory postsynaptic currents (EPSCs) were severely impaired in RIM-BP2 KO granule cell autapses as compared to that in WT autapses (Figure 5a,b). Rescue of RIM-BP2 deficiency by lentiviral expression in RIM-BP2 KO neurons completely restored synaptic transmission, confirming the specificity of RIM-BP2 function at these synapses (Figure 5a,b). To examine the origin of the impaired evoked response, we first probed vesicle priming by measuring the readily releasable pool (RRP) via hypertonic sucrose solution application. In line with the finding that RIM-BP2 KO MF synapses had only half the number of docked vesicles compared to that in WT neurons (Figure 4), the size of the RRP was significantly reduced (Figure 5c,d). The frequency and amplitude of Ca2+-independent release events as measured by recording spontaneous miniature EPSCs (mEPSCs) were not significantly altered upon RIM-BP2 loss (Figure 5h and Figure 5—figure supplement 2a). We next assessed vesicular release probability Pvr, as the ratio of EPSC and RRP charge, and RIM-BP2 KO and WT granule autapses were not significantly different (Figure 5d). However, utilizing paired-pulse ratio (PPR, 25 ms interstimulus interval), we found that RIM-BP2 KO neurons displayed enhanced facilitation compared to WT neurons, which could be rescued by re-expression of RIM-BP2 (Figure 5e,f). We assessed PPR in more detail by extending interstimulus intervals to up to 500 ms. At all but one interstimulus intervals tested (250 ms), PPF was increased (Figure 5g). Also, EPSCs evoked by 10 Hz action potential trains displayed less depression over the 5 s train duration in RIM-BP2 KO granule cell autapses compared to WT or rescue groups (Figure 5—figure supplement 2b,c). Thus, loss of RIM-BP2 leads to impaired hippocampal granule cell output, due to changes in both vesicle docking/priming and due to changes in release during repeated stimuli.

RIM-BP2 primes synaptic vesicles via Munc13-1 in granule autaptic neurons

Our gSTED imaging experiments revealed a decrease in presynaptic Munc13-1 clusters upon the loss of RIM-BP2 (Figure 3). In small central synapses, priming is attained by an interaction of Munc13 and RIM via the Munc13 C2A domain, which can be mimicked by the constitutively monomeric mutant Munc13-1 K32E lacking Munc13-1 homodimerization (Deng et al., 2011). To test whether vesicle priming can be rescued by restoring Munc13-1 function in RIM-BP deficient MF synapses, we lentivirally transduced Munc13-1 WT (M13WT) or the constitutively monomeric Munc13-1 mutant (M13K32E) (Camacho et al., 2017) in granule autapses. Remarkably, Munc13-1 K32E expression in RIM-BP2 KO granule neurons sufficed to rescue the RRP, whereas Munc13-1 WT was not sufficient to rescue vesicle priming upon RIM-BP2 deletion (Figure 6d). In line with the RRP, evoked release could not be rescued by Munc13-1 WT, but required the constitutive active form of Munc13-1 K32E (Figure 6a,b). Again, the Pvr was neither altered upon RIM-BP2 deletion nor by the rescue of Munc13-1 WT or Munc13-1 K32E (Figure 6d).

Figure 6
Download asset Open asset
Monomeric Munc13-1 rescues vesicle priming in RIM-BP2 KO granule autaptic neurons.

(a) Sample traces of evoked EPSC amplitudes before (black) and after DCG IV application (gray) for RIM-BP2 WT and KO neurons and lentiviral-transduced RIM-BP2 KO rescues with either Munc13-1 WT (M13WT) or Munc13-1 K32E (M13K32E). (b) Summary graphs of normalized EPSC amplitudes evoked by 2 ms depolarization (red arrow) (EPSC WT (49/3); KO (47/3); M13WT (18/2); M13K32E(41/3)) and after DCGIV application. (EPSC-DCG WT (49/3); KO (44/3); M13WT (18/2); M13K32E(41/3)) (c) Sample traces and (d) summary graphs of normalized RRP responses elicited by a 5 s application of 500 mM sucrose (RRP WT (41/3); KO (36/3); M13WT (17/2); M13K32E(39/3)). Summary graph of the PVR calculated as the ratio of the EPSC charge and the RRP charge (Pvr WT (41/3); KO (38/3); M13WT (16/2); M13K32E(37/3)). Values represent mean ± SEM. *p<0.05, **p<0.01. For statistics please see Figure 6—source data 1.

https://doi.org/10.7554/eLife.43243.025
Figure 6—source data 1

Statistics of data presented in Figure 6.

https://doi.org/10.7554/eLife.43243.026

These results suggest that in MF synapses, unlike hippocampal pyramidal neuron synapses, the recruitment or stabilization of active monomeric Munc13-1 is RIM-BP2 dependent.

Discussion

Chemical synapses have been highly diversified by evolution in their molecular composition, ultrastructure, and consequently function. In the last decades, presynaptic diversity was studied in synapses that exhibit ultrastructural differences, such as the T-bar structure in the neuromuscular junction of Drosophila melanogaster or the ribbon synapse of vertebrate photoreceptor cells (Ackermann et al., 2015). Ultrastructural diversity is often associated with the expression of specialized synaptic organizers, like Bruchpilot or RIBEYE, which shape presynaptic structure and function (Ackermann et al., 2015; Wagh et al., 2006; Schmitz et al., 2000). More recently, the heterogeneity of distinct synapses came into focus, since many central synapses seemingly express similar presynaptic proteins but still show distinct release probabilities and Ca2+-secretion coupling. Synaptic heterogeneity might be achieved by several mechanisms, including variation in the abundance of single proteins or expression of different protein isoforms. Notably, a contribution of the exact nanoscale arrangement of active zone proteins to synaptic diversity has also been discussed (Atwood and Karunanithi, 2002; Nusser, 2018).

To understand the function of a given protein in neurotransmitter release, one can compile the results from protein knockouts in diverse synapses and extract a universal function. Some highly conserved proteins, like Munc13-1, are essential for neurotransmitter release in a variety of synapses, since they exclusively conduct one specific function, in this case vesicle docking and priming (Augustin et al., 1999; Varoqueaux et al., 2002; Weimer et al., 2006; Aravamudan et al., 1999). However, some other presynaptic proteins show distinct knockout phenotypes for diverse synapses, like RIM-BPs. In small central synapses, the calyx of Held, and inner ear hair cells RIM-BP2 has rather minor effects on neurotransmitter release, by fine-tuning the coupling between Ca2+-channels and release sites (Acuna et al., 2015; Grauel et al., 2016; Davydova et al., 2014). Strikingly, we now show that in large MF synapses, the prevailing phenotype of RIM-BP2 loss is an impaired recruitment of Munc13-1 to the active zone, resulting in reduced vesicle docking, priming and consequently neurotransmission. Therefore, RIM-BP2 function depends on the synapse type where it is expressed.

Why does RIM-BP2 functions differ between hippocampal SC and MF synapses? We propose that differences in the structural organization of active zones might be responsible for the observed phenotypes. When comparing apparent distances between active zone protein clusters, clusters of the presynaptic scaffold proteins RIM-BP2 and Munc13-1 were found at larger distances at MF synapses as compared to SC synapses. Also, the distance of the closest neighboring cluster of RIM1 to a given Cav2.1 cluster is larger compared to the distance we previously found at SC synapses (Grauel et al., 2016). Therefore, our STED analysis suggests that a single active zone may contain more than one protein cluster of key active zone proteins. Some of these key players might have a differential relative localization between each other at MF synapses in comparison to SC synapses. However, further evidence of sub-active zone organization is required to verify this hypothesis. Moreover, more sophisticated methods of defining protein clusters to belong to the same active zone will be helpful in defining the architecture of the active zone of mammalian central synapses.

The exact physiological meaning of active zone protein cluster arrangement is still unresolved but may serve as a correlate to the observed phenotypic differences between WT and KO neurons. However, the distance measurements between clusters of vesicle docking/priming factor Munc13-1 and Ca2+-channels we retrieved at MF terminals were in the same range of what was previously reported in the NMJ and CNS of Drosophila (Fulterer et al., 2018), and were also similar to estimates for Ca2+-secretion coupling distances from physiological recordings using efficacy tests of slow Ca2+-chelators (Aravamudan et al., 1999).

gSTED analysis is superior in defining relative protein localization, but less precise in quantifying absolute protein levels based on fluorescence intensity. In confocal fluorescence measurements performed in parallel to gSTED imaging, we observed that loss of RIM-BP2 led to an overall reduction in Munc13-1 levels at MF synapses. This is in contrast to SC synapses and overall unchanged Munc13-1 levels by western analysis on synaptosomal fraction (Grauel et al., 2016). These combined results argue for a specific role of RIM-BP2 in stabilizing Munc13-1 at active zones of MF synapses and consequently the establishment of Munc13-1 clusters. This effect could be indirect via RIM, as it is known for SC synapses where vesicle priming is accomplished by the interaction of RIM1 and Munc13-1 independent of RIM-BP2 (Deng et al., 2011; Andrews-Zwilling et al., 2006), or perhaps through direct interactions via RIM-BP2, as previously shown in Drosophila (Böhme et al., 2016). A critical role of RIM-BP2 in Munc13 recruitment is consistent with the docking/priming phenotype of RIM-BP2 loss in the fly NMJ where the reduction in Munc13 levels is severe upon loss of RIM-BP (Liu et al., 2011). The electron micrographs from RIM-BP2 KO MF synapses revealed in addition to a 25% loss of docked vesicles, similarly to what has been previously shown for Munc13-1/−2 deficient central synapses (Imig et al., 2014). Putting this together with the gSTED analysis, we speculate that the MF synapse is more sensitive to reductions in Munc13-1 levels, leading to stronger impairment in forming functional Munc13-1 clusters.

Why are Munc13-1 levels differentially affected by RIM-BP2 deletion? One possible explanation is that the expression of interaction partners other than RIM-BP2 varies among synapses. For example, RIM, a critical interaction partner of Munc13-1, is less expressed in the MF synapses compared to SC synapses (Cembrowski et al., 2016), and therefore loss of RIM-BP2 cannot be redundantly supported by RIM-Munc13 interactions. In any case, the functional hierarchy of the triple complex formed by RIM-BP2/RIM1/Munc13-1 appears fundamentally different between SC and MF synapses. At MF synapses RIM-BP2 acts first to stabilize RIM1/Munc13-1 at the active zone, whereas at SC synapses, RIM-BP2 impacts synaptic function following RIM/Munc13-1 priming of SV vesicles at the active zone. However, RIM-BP2 dependent stabilization of Munc13-1 still requires RIM activity, since Munc13-1 K32E, the constitutively active form of Munc13-1, but not Munc13-1 WT, is sufficient to rescue the RIM-BP2 MF phenotype (Figure 6; and Deng et al., 2011; Andrews-Zwilling et al., 2006).

Another important question is, if RIM-BP2 alters synaptic release probability at MF terminals. Interestingly, relative Ca2+-channel localization at the MF synapses is not affected by the deletion of RIM-BP2, therefore the changes in release probability are rather due to increased coupling distances between Ca2+-channels and Munc13-1 as previously shown in C. elegans (Zhou et al., 2013). Also, the reduction in release probability might be due to the pronounced function of Munc13-2 in RIM-BP2 KO MF synapses (Rosenmund et al., 2002), since Munc13-1 clusters but not Munc13-2 clusters abundance and localization are altered upon RIM-BP2 deletion. Still unresolved is the discrepancy between PPR and Pvr measurements in RIM-BP2 deficient MF synapses. Either RRP and Pvr measurements are not correlating at MF granule neurons, or RIM-BP2 specifically alters processes related to PPR but not Pvr, as shown for the synaptic protein Rab3 (Schlüter et al., 2006).

In mammalian synapses and Drosophila NMJ, RIM-BPs have been shown to biochemically interact with Ca2+-channels (Liu et al., 2011; Davydova et al., 2014), resulting in a severe loss of overall Ca2+-channel densities at RIM-BP deficient NMJ’s (Liu et al., 2011). In contrast, central mammalian synapses show no discernable signs of Ca2+-channel dysfunction, but just moderate to weak changes in synaptic transmission, compatible with an impaired Ca2+-secretion coupling mechanism (Grauel et al., 2016; Davydova et al., 2014; Acuna et al., 2014). However, the effect is sufficiently strong to cause changes in short term plasticity properties, indicative of a role of RIM-BP2 in regulating release probability and short-term plasticity, similar to what has been observed by loss of the four mammalian rab3 genes (Schlüter et al., 2006).

It will be of interest to see whether and through which molecular mechanism loss of RIM-BP2 alters the function of other mammalian synapses in relation to their Ca2+-secretion coupling and vesicle priming. While it is clear that factors or structural motifs must exist that determine synaptic diversity such as observed in the described synapses, the composition and spatial organization of such active zone super-organizers remains to be determined.

Materials and methods

Key resources table
Reagent type
(species) or resource		DesignationSource or referenceIdentifiersAdditional
information
Genetic reagent (M. musculus)Rimbp2PMID: 27671655Prof. Christian Rosenmund, Prof. Dietmar Schmitz (Charité)
Recombinant DNA reagentf(syn)NLS-RFP-P2A-RIMBP2This paper
Recombinant DNA reagentf(syn)NLS-GFP-P2A-rMunc13.1-FlagPMID: 28489077
Recombinant DNA reagentf(syn)NLS-GFP P2A-Munc13.1 K32E-FlagPMID: 28489077
AntibodyBsn
(N-terminal)		AbcamRRID:AB_18600181:1200 (IHC)
AntibodyCav2.1
(rat aa1921-2212)		Synaptic SystemRRID:AB_26198411:500 (IHC)
AntibodyCav2.1
(rat aa1921-2212)		Synaptic SystemRRID:AB_26198421:500
AntibodyHomer1
(human aa 1–186)		Synaptic SystemRRID:AB_105497201:200 (IHC)
AntibodyMUNC13-1
(rat aa 3–317)		Synaptic SystemRRID:AB_8877341:150 (IHC)
AntibodyMUNC13-2
(rat aa 151–317)		Synaptic SystemRRID:AB_26198071:150 (IHC)
AntibodyRIM1
(rat aa 602–723)		BD PharmigenRRID:AB_23152841:200 (IHC)
AntibodyRIM-BP2 (rat aa 589–869)Kind gift of A. Fejtova and Eckart Gundelfinger (Leibniz Institute for Neurobiology, Magdeburg, Germany)1:600/1:1000 (IHC)
AntibodyZnT3
(mouse aa 2–75)		Synaptic SystemRRID:AB_21896651:500
AntibodyAnti mouse AF488InvitrogenRRID:AB_1384041:100/1:200 (gSTED)
1:400 (confocal)
AntibodyAnti guinea pig AF594InvitrogenRRID:AB_1419301:100/1:200 (gSTED)
1:400 (confocal)
AntibodyAnti rabbit ATTO647NActive MotifCat number #150481:100 (gSTED)

KO mouse generation

Request a detailed protocol

RIM-BP2 KO mouse generation, specific deletion of the Rimbp2 gene, and genotyping was performed as described previously (Grauel et al., 2016). All animal experiments were approved by the animal welfare committee of Charité Universitaetsmedizin Berlin and the Landesamt für Gesundheit und Soziales Berlin and carried out under the license (Berlin State Government, T0410/12; T0100/03).

Slice preparation and electrophysiological recordings

Request a detailed protocol

Acute hippocampal slices were prepared as described previously (Grauel et al., 2016). In brief, RIM-BP2 KO mice and wild-type littermates of both sexes (4–8 weeks) were anesthetized with Isofluorane and decapitated. The brain was quickly removed and chilled in ice-cold sucrose-artificial cerebrospinal fluid (sACSF) containing (in mM): 50 NaCl, 25 NaHCO3, 10 glucose, 150 sucrose, 2.5 KCl, 1 NaH2PO4, 0.5 CaCl2, and 7 MgCl2. All solutions were saturated with 95% (vol/vol) O2/5% (vol/vol) CO2, pH 7.4.

Slices (300 μm, sagittal or horizontal) were cut with a Leica VT1200S microtome (Wetzlar, Germany) and stored submerged in sACSF for 30 min at 35°C and subsequently stored in ACSF containing (in mM): 119 NaCl, 26 NaHCO3, 10 glucose, 2.5 KCl, 1 NaH2PO4, 2.5 CaCl2 and 1.3 MgCl2 saturated with 95% (vol/vol) O2/5% (vol/vol) CO2, pH 7.4, at RT. Experiments were started 1 to 6 hr after the preparation.

Experiments were conducted in parallel on a comparable number of slices from WT and KO animals prepared at the same experimental day for at least 3 times (biological replicates). Technical replicates were obtained for evoked responses and averaged.

For recordings, slices were placed in a recording chamber continuously superfused with ACSF at RT at a rate of 2.5 ml/min. fEPSPs were evoked by electrical stimulation with patch pipettes filled with ACSF. fEPSPs were recorded with a low-resistance patch-pipette filled with ACSF. Recordings were performed with a MultiClamp 700B amplifier. Signals were filtered at 2 kHz and digitized (BNC-2090; National Instruments Germany GmbH) at 10–20 kHz. IGOR Pro software was used for signal acquisition (WaveMetrics, Inc).

For Mossy fiber recordings, stimulation electrodes were placed in the granule cell layer or in the hilus region. For fEPSP recordings, the recording electrode was placed in stratum lucidum of CA3 region. Mossy fiber origin of recorded signals was verified by frequency facilitation >400% when stimulus frequency was changed from 0.05 to 1 Hz and a complete block of responses upon DCG IV (1 µM; Tocris) application at the end of each experiment. Whole-cell recordings in voltage-clamp mode were performed in CA3 pyramidal cells, with an intracellular solution containing (in mM): K-Gluconate 120; Hepes 10; KCl 10; EGTA 5; MgSO4 2; MgATP 3; NaGTP one and Na-Phosphocreratine 5. Cells were held at −60 mV and series resistance was monitored by delivery of voltage steps prior to each evoked current. Mossy fiber signals were verified by pronounced frequency facilitation and paired pulse facilitation as well as by sensitivity to DCG IV. Paired pulse ratio (50 ms inter-stimulus interval) was measured on the average trace of 20 evoked currents (including possible failures). Failure rate was calculated in 30 traces by detecting the number of traces in which stimulation failed to induce an EPSC. fEPSPs in CA1 were recorded in stratum radiatum after stimulation of the Schaffer collaterals. fEPSPs of associative commissural fibers in area CA3 were recorded in stratum radiatum after stimulation electrodes were places in stratum radiatum of CA3, in the presence of DCG IV (1 µM) to avoid mossy fiber contamination. Amplitudes of EPSCs and fEPSPs were determined by analyzing ±2 ms of the amplitude peak. Data were analyzed with the Igor plug-in NeuroMatic (http://neuromatic.thinkrandom.com/) software. Recordings were only analyzed if the fiber volley remained constant throughout the recording. Statistical analysis was performed with Prism 6 (GraphPad Software).

Autaptic granule cell culture

Request a detailed protocol

Autaptic cultures of Dentate Gyrus Granule cells were prepared as described previously (Rost et al., 2010). In brief, the dentate gyrus of P0-P1 RIM-BP2 WT and KO embryos was separated from the hippocampus. After digestion with Papain and trituration, cells were plated on astrocytic micro-islands (Arancillo et al., 2013). Neurons were incubated at 37°C for 14–20 days before the electrophysiological characterization was performed. For rescue experiments, neurons were transduced with lentiviruses 24 hr after plating.

Lentiviral constructs

Request a detailed protocol

Lentiviral constructs used in this study were based on the FUGW vector (Lois et al., 2002). The cDNA from mouse RIM-BP2 (NM_001081388) and from rat Unc-13a (NM_022861) (Camacho et al., 2017) were cloned into an lentiviral shuttle vector after a NLS-GFP-P2A or NLS-GFP-P2A under the control of a human synapsin-1 promoter. The expression of nuclear RFP or GFP allows to identify transduced neurons. All lentiviruses were provided from the Viral Core Facility of the Charité Berlin and prepared as described before (Lois et al., 2002).

Electrophysiological recordings of autaptic neurons

Request a detailed protocol

To pharmacologically identify autaptic granule cells, DCG IV (1 µm) was washed in after each experiment. Only cells where synaptic transmission was inhibited by 70% or more were considered for analysis (Rost et al., 2010).

Whole-cell patch-clamp recordings in autaptic neurons were performed as described previously (Grauel et al., 2016) at 13–21 days in vitro (DIV) with a Multiclamp 700B amplifier (Molecular Devices). Data were acquired from at least three different cultures (biological replicates). To minimize variability in recordings, about the same number of autapses were recorded from each experimental group each day. Technical replicates were obtained for evoked responses and averaged. Data were normalized to the mean value of the control group of each culture.

The patch pipette solution contained the following (in mM): 136 KCl, 17.8 HEPES, 1 EGTA, 4.6 MgCl2, 4 Na2ATP, 0.3 Na2GTP, and 12 creatine phosphate, and 50 U/ml phosphocreatine kinase (300 mOsm; pH 7.4). The recording chamber was constantly perfused with extracellular solution containing 140 mM NaCl, 2.4 mM KCl, 10 mM Hepes, 2 mM CaCl2, 4 mM MgCl2, and 10 mM glucose (pH adjusted to 7.3 with NaOH, 300 mOsm). Solutions were applied using a fast-flow system. Data were filtered at 3 kHz, digitized at 10 kHz, and recorded with pClamp 10 (Molecular Devices). Data were analyzed offline with Axograph X (AxoGraph Scientific) and Prism 6.

EPSCs were evoked by a 2 ms depolarization to 0 mV from a holding potential of −70 mV. PPRs were calculated as the ratio from the second and first EPSC amplitudes with an interstimulus interval of 25 ms. The RRP size was calculated by integrating the transient current component of 5 s evoked by application of extracellular hypertonic 500 mM sucrose solution. Miniature EPSC (mEPSC) amplitude and frequency were detected using a template-based algorithm in Axograph X.

Immunohistochemistry, time gated STED microscopy and image analysis

Request a detailed protocol

Immunohistochemistry was performed as described previously (Grauel et al., 2016). Notably, the antibody against RIM1 (RRID: AB_2315284, BD Pharmigen) used in this study is not commercially available anymore. To repeat these results, other RIM1 antibodies need to be validated beforehand. Conventional confocal tile scans of RIM-BP2 immunofluorescence in the hippocampus were acquired with a Leica SP8 laser confocal microscope equipped with a 20 × 0.7 N.A. oil immersion objective.

Following immunostaining, sagittal cryosections (10 μm) of RIM-BP2 WT and KO brains were imaged by gSTED with a Leica SP8 gSTED microscope (Leica Microsystems) as described previously (Grauel et al., 2016). Within each independent experiment, RIM-BP2 KO and WT samples were imaged with equal settings. Single optical slices were acquired with an HC PL APO CS2 100×/1.40 N.A. oil objective (Leica Microsystems), a scanning format of 1,024 × 1,024, eight bit sampling, and 4.5 zoom, yielding a pixel dimension of 25.25 nm and 25.25 nm in the x and y dimensions, respectively. Four to eight super-resolved images were acquired per a single brain section of each mouse analyzed (n indicates the number of mice analyzed per each data set). MF were imaged in the CA3 stratum lucidum close to CA3 pyramidal cell bodies, where MF boutons make contact on proximal dendritic spines of CA3 pyramidal neurons. CA3-CA1 synapses were acquired in the CA1 stratum radiatum. Raw dual- and triple-channel gSTED images were deconvolved with Huygens Professional software (Scientific Volume Imaging) using a theoretical point spread function automatically computed based on pulsed- or continuous-wave STED optimized function and the specific microscope parameters. Default deconvolution settings were applied.

Experiments were performed at least two times on different mice (biological replicates).

For cluster distance analysis, deconvolved images were thresholded and segmented by watershed transform with Amira software (Visualization Sciences Group) to identify individual clusters and to obtain their x and y coordinates. Within the same independent experiment, the same threshold and segmentation parameters were used. According to the lateral resolution achieved, clusters with a size smaller than 0.0025 μm2 were not considered for analysis. To select Munc13-1 and CaV2.1 clusters within the ZnT3 +area, a mask was created applying a threshold on deconvolved ZnT3 +confocal images with Amira software (Visualization Sciences Group). Hundreds to thousands of clusters per single image were automatically analyzed. The average number of clusters at specific distances and the k-nearest neighbor distance were analyzed with a MATLAB custom-written script, as previously described (Grauel et al., 2016). More in details, in the first step the script determined the Euclidean distance between all possible cluster pairs in two channels in a matrix. The number of clusters in channel 1 found within 50 nm, 75 nm, 100 nm, 125 nm, 150 nm, 200 nm and 300 nm distances from each single cluster of channel two was calculated and averaged for all particles found in channel 2. To precisely identify at which specific distance changes in clustering may occur, the mean number of channel one clusters found at sampling distances from channel two was expressed in distance intervals (0–50 nm, 50–75 nm, 75–100 nm, 100–125 nm, 0.125–200 nm and 200–300 nm). K-nearest neighbor distance analysis was similarly based on the matrix containing the distances between all particles in both channels: the distances of all particles in channel one to the ones in channel two were sorted in ascending order to find the k-nearest neighbor. K was set to 1, 2, 3, 4 and 5. The k distance values were then averaged on the number of clusters in channel 2. Values retrieved for each image were then averaged per mouse. Data from independent experiments were pooled.

Line profile measurements of distances between clusters was performed in Imagej (NIH) on the same deconvolved gSTED images used for the semi-automated analysis. Well defined side view or planar synapses within areas with high density of active zones corresponding to MF synapses were manually traced with the line profile tool (thickness 10 pixels/~250 nm), using the ImageJ Macro (Macro_plot_lineprofile_multicolor from Kees Straatman, University of Leicester, Leicester, UK). Intensity values from individual synapses were exported to Excel. Up to six line profiles per image were consider for analysis. Local maxima were calculated with the SciPy ‘argrelmax’ function in order to obtain peak intensities for different image channels and peak-to-peak distances. Values were then averaged per mouse. Code has been made available via Github: (Gimber, 2019; copy archived at https://github.com/elifesciences-publications/LineProfileAnalysisWorkflow).

Measurements of Munc13-1 intensity were performed in ImageJ (version 1.51 w) on confocal images acquired in parallel to the gSTED images. Mean pixel gray values were measured for each whole image (25.83 µm x 25.83 µm). Four to eight confocal images per mouse were quantified and values averaged per mouse. Data from independent staining were pooled and analyzed.

Electron microscopy

Request a detailed protocol

Acute Hippocampal slices (150 µm) were prepared as described above and frozen at RT using an HPM 100 (Leica) supported with extracellular solution containing 15% Ficoll.

Slices from at least three different WT and KO animals were frozen and processed in parallel (biological replicate). After freezing, samples were transferred into cryovials containing 1% glutaraldehyde, 2% osmium tetroxide, and 1% ddH2O in anhydrous acetone in an AFS2 (Leica) with the following temperature program: −90°C for 72 hr, heating to −60°C in 20 hr, −60°C for 8 hr, heating to −30°C in 15 hr, −30°C for 8 hr, heating to −20°C in 8 hr. After staining with 1% uranyl acetate, samples were infiltrated and embedded into Epon and backed 48 hr at 60°C. Serial 40 nm sections were cut using a microtome (Leica) and collected on formvar-coated single-slot grids (Science Services GmbH). Before imaging, sections were contrasted with 2.5% (wt/vol) uranyl acetate and lead citrate. Samples were imaged in a FEI Tecnai G20 TEM operating at 80–120 keV and images taken with a Veleta 2K x K CCD camera (Olympus) and analyzed with a custom-written ImageJ (NIH) and MATLAB (The MathWorks, Inc) script. The size of the post-synaptic density is defined as the length of the prominent electron dense material at the post-synaptic side of the synapse. Small clear vesicles were defined by their diameter between 30–55 nm, whereas large clear vesicles were defined >60 nm.

Statistical analysis

Request a detailed protocol

For electrophysiological experiments in brain slices, numbers of experiments are indicated in n/N, while n represents the number of brain slices and N the number of animals. Sample size estimation was done as published previously (Breustedt et al., 2010).

For confocal and gSTED analysis, statistical analysis was done with Prism (Graphpad) and SPSS Statistics software (IBM), respectively. Normality was assessed checking histograms and Q-Q plots. Pairwise comparisons were analyzed with the Mann–Whitney U test. Significance threshold α was set to 0.05. Only p values less than 0.05 were considered significant. Values corresponding to one WT animal measured displaying an extreme outlier were excluded from the whole MF Munc13-1/CaV2.1 data analysis, based on SPSS estimation of extreme values (value >Q3+3*IQR). This WT mouse was excluded also from Munc13-1 intensity measurements at MF terminals. Values are expressed as mean ± SEM, and n indicates the number of animals tested. Sample size estimation was done as published previously (Grauel et al., 2016).

For autaptic electrophysiological experiments, statistical analysis was done in Prism (Graphpad). First, the D'Agostino-Pearson test was applied to check whether data are normally distributed. If data were normally distributed, statistical significance was determined by using one-way ANOVA followed by Turkey post hoc test. For data which were not normally distributed, statistical significance was assessed using non-parametric Kruskal-Wallistest with Dunn's post hoc test. Values are expressed as mean ± SEM, and n indicates the number of recorded autapses. Sample size estimation was done as published previously (Camacho et al., 2017; Liu et al., 2016).

For electron microscopy experiments, the D’Agostino–Pearson omnibus test was used to check for normal distribution of data. For WT vs. KO comparison, an unpaired t test with Welch’s correction was used for normally distributed data and the Mann–Whitney U test was used for not normally distributed data. Values are expressed as mean ± SEM, and n indicates the number of active zones analyzed. Sample size estimation was done as published previously (Grauel et al., 2016).

Data availability

All data generated are shown as scatter plots in each graph. Code has been made available via Github (https://github.com/ngimber/LineProfileAnalysisWorkflow/releases/tag/1.0.0; copy archived at https://github.com/elifesciences-publications/LineProfileAnalysisWorkflow).

References

Decision letter

  1. Marlene Bartos
    Reviewing Editor; University of Freiburg, Germany
  2. Gary L Westbrook
    Senior Editor; Oregon Health and Science University, United States
  3. Craig Curtis Garner
    Reviewer; German Center for Neurodegenerative Diseases, Germany

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses" for consideration by eLife. Your article has been reviewed by Gary Westbrook as the Senior Editor, a Reviewing Editor, and three reviewers. The following individual involved in the review of your submission has agreed to reveal his identity: Craig Garner (Reviewer #2). The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

The project investigates the functional role of the presynaptic scaffold protein RIM-BP2 at three hippocampal synapses. The authors report that deletion of RIM-BP2 mossy fiber (MF) synapses strongly impairs neurotransmission. In contrast, input-output function at other excitatory hippocampal synapses was not impaired. The data are confirmed in cultured neurons forming autapses, where it is further shown that lentiviral expression of Munc13-1KE bypasses the need for RIM-BP2. Finally, the authors provide STED analyses in slices, where they assess protein cluster localization by applying the 'nearest neighbor analyses' (NN), and find changes in Munc13-1 clusters, but not in Munc13-2, Ca channels and RIM clusters. Although the reviewers judged the observation that RIM-BP2 has important roles in synaptic release specifically at MF terminals as interesting, they had several major concerns, which will be summarized in the following:

1) In general, the reviewers found the description of many experiments very superficial, lacking sufficient information for comprehending the way the conclusions were reached. The illustrations of the findings are also suboptimal. (a) For example, the authors did not even mention the experiments described in Figure 6C,D in the Results section. (b) In Figure 4 the EM images illustrating the synapses are very small. The authors should present low power images to provide an overall view of the tissue, and provide multiple high power images of many synapses. (c) Why did the authors use high-pressure cryofixation? Please explain. (d) The authors quantitatively analyze the distribution of RIM, Cav2.1 and homer clusters. The description of these experiments is extremely superficial in the Results section. (e) The reader could not figure out how many synapses from how many slices and from how many animals the authors analyzed. (f) There is a lack of information in the results or the legends about the way the authors clustered their data. Finally, the manuscript contains many typos and language imprecisions and therefore requires very carefully edited.

2) Two reviewers formulated significant concerns about the STED analysis, which needs very careful revision. The reviewers wish to see data on how many clusters they find, what method was used for determining the clusters, how the distances between clusters has been measured and more importantly how the authors distinguished between clusters within an active zone and between active zones. The manuscript must be improved in this respect. Detailed comments see below in A-C.

A) The NN-STED analysis is not very meaningful at MF terminals. While NN is insightful for methods that localize individual molecules, it is not for STED, which does not have this capacity. It is uncertain whether any protein cluster is within MF terminals or may be in other synapses around. The nature of biochemical interactions of these proteins suggests that they are intermixed as they all bind to one another, it is not clear that there are separable RIM or CaV2 or Munc13 clusters at distances of 200 nm of each other within an active zone. It is also not clear whether clusters of different proteins belong to the same active zone or even the same synapse. Some of these points are reflected in the data. In Figure 2, it is unclear how RIM, on average, ends up being closer to Homer1 than to CaVs, if the three belong to the same synapse (CaVs sit in the membrane that separates RIM and Homer). Figure 3 claims a reduction in Munc13 levels, but what the author's measure in their analysis is cluster numbers, not levels. It would be much preferable to have a measurement of Munc13 levels within a bouton or within an active zone. This could easily be done in experiments in cultured Dentate Gyrus neuron autapses. The authors should provide either the information on cluster analyzes or find a better way to analyze their STED images.

B) On similar lines: One fundamental issue relating the overall conclusion is the number of clusters of each molecules and their spatial separations within the AZ. Given an average AZ area of 0.06 um2, the diameter of such average AZ (assuming disc shape) would be ~280 nm. The authors do not tell the number of clusters for each proteins, but their separation distances are around 260 and 110 nm. The reviewer would like to see the number of clusters per AZ for each presynaptic AZ molecules and their spatial arrangements that is compatible with the measured inter-cluster distances. Without knowing the numbers, the reviewer cannot comprehend whether such cluster separation distances can be consistent with the size of the AZ or not.

C) How were distances between 'clusters' measured? For example, bassoon seems to form a homogeneous line in Supplementary Figure 1A and RIM-BP and Munc13-1 form some clusters. The authors should demonstrate on the figure how they measured these distances and they should provide more images from which the readers could have an impression of how similar or dissimilar the synapses were with respect to these proteins.

Related to the problem of cluster distance quantification: The authors performed two sets of colocalization experiments: Cav2.1 vs. RIM1 and Munc13-1 vs. RIM BP2. The distances between these clusters were ~ 250 and 170 nm. What is the spatial relationships among them?

3) Another major shortcoming of the manuscript is the lack of detailed demonstration of how RIM-BP2 affects Schaffer collateral (SC) synapses. First, the authors did not perform all localization experiments in SC synapses in parallel with that of mossy fiber synapses. In addition, no functional experiment is presented that would test the prediction of the altered molecular composition of the SC synapses. Please provide the comparative functional data.

4) A further important addition is to do a better paired-pulse ratio (PPR) analysis in cultured dentate gyrus neurons to assess probability of vesicular release (Pvr). The increased PPR strongly suggest a decrease in Pvr, but the analysis is limited to a single inter-spike-interval. The authors use the sucrose method as a measure of Pvr and argue that Pvr is unchanged, but it remains unclear whether this is a valid way to quantify Pvr at cultured dentate gyrus synapses. A complete analysis of PPRs at cultured dentate gyrus neurons and in hippocampal slices should be performed at various inter-stimulus intervals. This would better connect the slice and culture data sets, and could either support decreased Pvr, or reject this hypothesis. If PPRs indicate decreased Pvr, then this should be better stated in the Title and the Abstract.

Full reviews included for reference:

Reviewer #1:

This study investigates the functional role of the presynaptic scaffold RIM-BP2 at three hippocampal synapses. The authors report that deletion of RIM-BP2 strongly impairs mossy fiber neurotransmission, but input-output function at other excitatory hippocampal synapses is not impaired. These phenotypes are confirmed in cultured autaptic neurons, where it is further shown that lentiviral expression of Munc13-1KE bypasses the need for RIM-BP2. Finally, the authors provide STED analyses in slices, where they assess protein cluster localization with "nearest neighbor analyses" (NN), and find changes in Munc13-1 clusters, but not Munc13-2, Ca channels and RIM.

The observation that RIM-BP2 has important roles in release specifically at mossy fiber synapses is interesting, relevant, and established with the represented work. I strongly support publishing this finding in eLife. However, the paper has several problems that should be addressed first. While only a limited number of experiments are needed, particularly the analyses of the STED data is problematic. While a link to Munc13 appears likely, this needs to be better addressed, Abstract and Title should express that this is likely indirect, and it should be better discussed upfront that the phenotype probably arises from a combination of reduced RRP and reduced pvr.

1) The NN STED analysis is not very meaningful at MF terminals. While NN is insightful for methods that localize individual molecules (storm, palm or immuno-gold EM), it is not for STED which does not have this capacity. It is uncertain whether any protein cluster is within MF terminals or may be in other synapses around. More, the nature of biochemical interactions of these proteins suggests that they are intermixed as they all bind to one another, it is not clear that there are separable RIM or CaV2 or Munc13 clusters at distances of 200 nm of each other within an active zone. It is also not clear whether clusters of different proteins belong the same active zone or even the same synapse. Some of these points are reflected in the data. In Figure 2, it is unclear how RIM, on average, ends up being closer to Homer1 than to CaVs if the three belong to the same synapse (CaVs sit in the membrane that separates RIM and Homer). Figure 3 claims a reduction in Munc13 levels, but what the authors measure in their analysis is cluster numbers, not levels. In the end, it would be much preferable to have a measurement of Munc13 levels within a bouton or within an active zone. This could easily be done in experiments in cultured dg neuron autapses. The authors should also find a better way to analyze their STED images, or remove the current analysis.

2) Most aspects of the phenotype look like a "reduced RIM-phenotype" in the RIM-BP mutants: A reduction in RRP, loss of docked and tethered vesicles (Munc13 knockouts only have a loss of vesicles within 2 nm and increased vesicles within 5-30 nm), and the phenotype can be bypassed with KE Munc13 (which mimics monomeric Munc13 that is independent of RIM) but not regular Munc13 (which requires RIM for activation). These data strongly predict reduced RIM levels or aberrant RIM localization in MF terminals upon RIM-BP2 KO, the only experiment that speaks against this the STED nearest neighbor analysis, but see 1. RIM localization and levels should be better assessed, the most straightforward would be to do this in dg autapses.

3) The increased paired pulse ratios strongly suggest a decrease in pvr (but the analysis is limited to a single ISI and hence not very strong). The authors use the division of the EPSC by the sucrose EPSC as a measure of pvr and argue that pvr is unchanged, but I could not find literature to establish that it is valid to quantitatively determine pvr at cultured dg synapses using this indirect method. Reduced pvr in addition to the RRP deficit makes sense in terms of everything that is known about RIM-BP and its roles, its interactions with RIM, and the observed PPR changes in Figure 5. A complete analysis of PPRs at cultured dg neurons and in hippocampal slices should be performed at various interstimulus intervals. This would better connect the slice and culture data sets, and could either support decreased pvr, or reject this hypothesis. If PPRs indicate decreased pvr, this should be better stated in Title and Abstract, there is no need for RIM-BP to have an isolated effect on RRP for this study to be interesting.

Reviewer #2:

This manuscript describes experiments to compare the contribution of RIM-BP2 to synaptic transmission at DG-CA3 mossy fiber (MF) boutons to small CA3-CA1 excitatory synapses. Electrophysiological and morphological studies reveal that RIM-BP2 loss of function only modestly affect CA1 synaptic transmission and Ca2+ secretion coupling, while its loss at MF boutnd has a strong impact on neurotransmitter release by promoting SV docking and priming via Munc13-1. The data collected strongly supports the claims of the authors, namely that the nano-environment and complexes formed by RIM-BP2 with the active zones of these two synapse, imparts function differences. Although molecular diversity at synapses has been long thought to be a possible mechanism for contributing to functional difference at synapses, there are few examples where this has been demonstrated to be the case. This study thus provides compelling evidence that RIM-BP2 is one such regulator.

Over all the data presented are of very high quality. A particular strength is the combination of data from acute slices, where the identity of each synapses is well established, and autaptic cultures with the electrophysiological properties of neurotransmitter release can be best evaluated. Also strong are the EM and superresolution data, providing information on changes in molecular distances of different active zone proteins and docking of SVs.

One concern requiring some attention is the author's use of the term levels of synaptic protein. (e.g. Results section; Discussion section). It is not self-evident that any measures of levels were perform. Cluster # yes, but no intensity values. This should be amended. Also, any statement on changes in levels should Western data in addition to (Discussion section) RNAseq data, which would reflect changes in expression levels of these key proteins.

Reviewer #3:

The present MS describes physiology and anatomy experiments, addressing the role of RIM-BP2 in neurotransmission. The authors demonstrate that the loss of RIM-BP2 has a differential effect in hippocampal MF vs. SC synapses, suggesting that the same protein could serve different roles in distinct central synapses. The combined superresolution gSTED microscopy and electrophysiology approach is powerful in revealing potential molecular mechanisms underlying distinct function. In general, the reviewer finds the description of many experiments very superficial, lacking sufficient information for comprehending the way the conclusion was reached. The illustrations of the findings are also suboptimal.

One fundamental issue relating the overall conclusion is the number of clusters of each molecules and their spatial separations within the AZ. Given an average AZ area of 0.06 um2, the diameter of such average AZ (assuming disc shape) would be ~280 nm. The authors do not tell the number of clusters for each proteins, but their separation distances are around 260 and 110 nm. The reviewer would like to see the number of clusters per AZ for each presynaptic AZ molecules and their spatial arrangements that is compatible with the measured inter-cluster distances. Without knowing the numbers, the reviewer cannot comprehend whether such cluster separation distances can be consistent with the size of the AZ or not.

It seems that the authors are not aware of the fact that hippocampal MF AZs contact distinct postsynaptic target cell types with very different functional properties. It was surprising to read that the authors lumped together all MF AZs irrespective of their postsynaptic target cells.

Another major shortcoming of the MS is the lack of detailed demonstration of how RIM-BP2 affects SC synapses. First, the authors did not perform all localization experiments in SC synapses in parallel with that of MF synapses. In addition, no functional experiment is presented that would test the prediction of the altered molecular composition of the SC synapses.

The authors analyse the distribution of RIM, Cav2.1 and homer clusters quantitatively. The description of these experiments is extremely superficial in the Results section. The reader cannot figure out how many synapses from how many slices and from how many animals the authors analysed. Nothing is written in the results or the legends about the way they clustered their data. Similar, the reader has no idea about the way the authors measured distances between such 'clusters'. For example, bassoon seems to form a homogeneous line in Supplementary Figure 1A and RIM-BP and Munc13-1 form some clusters. The authors should demonstrate on the figure how they measured these distances and should also provide more images from which the readers could have an impression of how similar or dissimilar the synapses were with respect to these proteins.

The reviewer has problems understanding the beautiful LM gSTED images. For example, in Figure 3G, the entire area seems to be tiled with green and red areas. How can the authors determine the boundaries of synapses? Where does one end and the second starts?

In subsection “RIM-BP2 docks synaptic vesicles via the specific recruitment of Munc13-1 at MF Synapses”, the authors describe a large change in the distance between Cav2.1 and Munc13-1 clusters. From the image in Figure 3A, the most dramatic effect of RIM-BP KO is the reduction of Munc13-1 protein. The functional interpretation of these two effects is completely different. The first would indicate a much reduced Pv whereas the second a dramatic reduction in N (number of docking sites).

Many parts of the experiments are superficially described in the manuscript. For example, the authors did not even mention the experiments described in Figure 6C,D in the Results section.

The authors describe the quantification of their gSTED data on bassoon, Munc13-1 and RIM-BP2 in Supplementary Figure 1. The illustration of that data together with those obtained in KO mice should be moved to the main figures.

The authors performed two sets of colocalization experiments: Cav2.1 vs. RIM1 and Munc13-1 vs. RIM BP2. The distances between these clusters were around 250 and 170 nms. What is the spatial relationships among them (see my major point as well)?

Figure 2B, Figure 3B,C,H,I: The authors should not present their data as% of control, but should show the number of clusters they detect.

Figure 4: The EM images illustrating the synapses are very small. The authors should present low power images to provide an overall view of the tissue and also have multiple high power images of many synapses.

Why did the authors use high-pressure cryofixation?

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses" for further consideration at eLife. Your revised article has been favorably evaluated by Gary Westbrook (Senior Editor), a Reviewing Editor, and three reviewers. The manuscript has been improved but there are a few remaining issues that we would like you to address before acceptance. For your information, we have also included the comments of the reviewers prior to the reviewer/editor discussion.

Summary:

After careful re-reading of the revised manuscript, all reviewers acknowledge the revision by the authors, the importance of the study and the fact that the study should be published at eLife. However, all reviewers agreed that the details of the image analysis and cluster analysis could be improved. The limitation being that it is unclear whether a cluster belongs to the same active zone or not. Therefore, please further discuss the details of the cluster analysis. In this context, please tone down the importance of the cluster analysis in the Abstract. Moreover, emphasize the problem with the availability of the RIM antibody that readers understand the limitations.

Reviewer #1:

I continue to strongly support this paper and it is fine to accept it at ELife as is. The observation that RIM-BP2 knockout has strong effects on MF but not other hippocampal excitatory synapses, and that this role is mediated through Munc13-1 is interesting and important. There are a few points, however, the authors may want to consider:

a) I continue to think that there is too much emphasis on the nearest neighbor analysis. The authors now do a good job in describing some of its limitations, but I am still not convinced that the fundamental assumption that underlies this analysis – that there are separable clusters of RIM-BP, CaVs, Munc13s, etc. within an active zone – makes sense, at least not for all of this proteins. It is fine for me to remain in disagreement on this point. The paper has a very important message regardless.

b) Subsection “RIM-BP2 docks synaptic vesicles via the specific recruitment of Munc13-1 at MF synapses”: the docking deficit is ~25%, not 50%, and the text refers to the wrong figure panel.

Reviewer #2:

In the revised manuscript the authors have thoroughly addressed each of the concerns raised by the previous reviewers. In its currently form the data presented in the manuscript strongly support the author's conclusions. In brief, they have examined whether the molecular diversity of active zones could contribute to difference in synaptic function. Here they focused on the contribution of RIM-BP2 at hippocampal mossy fiber and small CA1 synapses. While RIM-BP2 loss of function has only modest effects on CA1 synapses, it loss at MF boutons results in quite profound changes in synaptic transmission. Their light, EM, super-resolution and functional analysis point to prominent role for RIM-BP2 in positioning Munc13-1 at MF synapses but not at CA1 synapses. Importantly, associated defects at MF-synapse can be rescued by a constitutively active Munc13 (K32E) indicating that RIM-BP2 faciliates the localization and activation of Munc13-1 at these synapses.

Overall this is a very nice manuscript that reads well and support the major claims of the authors. I would support the publication of this manuscript in it current form, without the addition of new data.

Reviewer #3:

In their rebuttal, the authors pulled together the comments of the three reviewers in an unusual way and aimed to address the concerns together. This hampered to comprehension of the responses a bit and also lead to some confusions! It seems that even the authors were confused by the way they addressed the concerns!

Intra- or inter-release site clustering: The authors admit that they do not really know which clusters are within an AZ and which ones are in different AZs. They argue that because the mean AZ diameter is 390 nm therefore two clusters that are within this distance must belong to one AZ and the ones with larger separation are in separate AZs. This is an incorrect and way oversimplified argument. First, without knowing the inter AZ distance distribution, such statement cannot be made. If the shortest inter-AZ distance is only 250 nm, then an inter-cluster distance of 300 nm might still reflect an inter-AZ arrangement. Second, as the authors pointed out this 390 nm is the mean AZ diameter. It is well known that there is tremendous variability in the AZ diameters, thus even a 500 nm inter-cluster distance could still represent a within-AZ arrangement in large AZs.

Although the authors argue that now they can determine the number of clusters per AZ for many proteins, the reviewer is not convinced. One is the consequence of the uncertainty of delineating AZs (see above) and the second is the lack of convincing demonstration of the objective clustering.

The authors misinterpreted the reviewer's concern regarding the distinct postsynaptic targets of MFs. Indeed, the reviewer referred to the fact that granule cell axons contact CA3 PNs as well as a large variety of GABAergic INs. The important point is that the functional and structural properties of these synapses are highly heterogeneous. Thus, the population comparisons of the function (field EPSP) to random gSTED images is fundamentally flawed. Meaningful comparisons would require the molecular identification of every postsynaptic target cell type in the STED experiments and the intracellular recordings all possible postsynaptic cell types (CA3 PNs and every type of INs).

https://doi.org/10.7554/eLife.43243.029

Author response

[…] Although the reviewers judged the observation that RIM-BP2 has important roles in synaptic release specifically at MF terminals as interesting, they had several major concerns, which will be summarized in the following:

1) In general, the reviewers found the description of many experiments very superficial, lacking sufficient information for comprehending the way the conclusions were reached. The illustrations of the findings are also suboptimal. (a) For example, the authors did not even mention the experiments described in Figure 6C,D in the Results section. (b) In Figure 4 the EM images illustrating the synapses are very small. The authors should present low power images to provide an overall view of the tissue, and provide multiple high power images of many synapses. (c) Why did the authors use high-pressure cryofixation? Please explain. (d) The authors quantitatively analyze the distribution of RIM, Cav2.1 and homer clusters. The description of these experiments is extremely superficial in the Results section. (e) The reader could not figure out how many synapses from how many slices and from how many animals the authors analyzed. (f) There is a lack of information in the results or the legends about the way the authors clustered their data. Finally, the manuscript contains many typos and language imprecisions and therefore requires very carefully edited.

We thank the reviewers for raising these points. We restructured the text and added more information to describe each conducted experiment in more details.

a) We are sorry to have omitted this point. The description of the graph is now added to the current manuscript.

b) For a better illustration of the EM results, we added more pictures for MF synapses with low and high resolution (Figure 4).

c) In the present study, we choose to perform our EM analysis of docked synaptic vesicles using highpressure freezing with subsequent chemical freeze substitution. High pressure freezing emerged in recent years as a new standard in the analysis of synaptic structures, and in particular in description of processes such as synaptic vesicle docking. The main reasons are that this approach appears to have less experimental artifacts. See for example effects of deletion of Munc13 leads in chemical fixation to no changes in vesicle docking, while it does so in high pressure frozen samples (Camacho et al., 2017; Varoqueaux et al., 2002). As structures are arrested on a ms time scale movement, diffusion-based artifacts are reduced. Second, chemical fixation dehydrates the fixed tissue, induces more sample shrinkage and triggers synaptic vesicle fusion due to hyperosmolarity of fixation solutions.

d) We agree with the reviewers and included a more detailed description of these experiments in the main text and in the figure legend, inclusive of a new data analysis (Figure 2D-H).

e and f) In the first version of our manuscript, we stated the data processing and number of conducted experiments exclusively in Supplementary file 1, in the statistics and in the method part. We now added the number of biological replicates per group to the figure legends, to provide better accessibility to this information. We also included more information regarding our experiments and analysis in the Material and methods section.

2) Two reviewers formulated significant concerns about the STED analysis, which needs very careful revision. The reviewers wish to see data on how many clusters they find, what method was used for determining the clusters, how the distances between clusters has been measured and more importantly how the authors distinguished between clusters within an active zone and between active zones. The manuscript must be improved in this respect. Detailed comments see below in A-C.

We thank the reviewers for raising these important points and appreciate the possibility to explain our strategy point by point:

1) Definition of protein clusters and determination of cluster distances:

We identified protein clusters in deconvolved 2D gSTED images based on an uneven fluorescence signal distribution. We used thresholding of single channel images, followed by watershed segmentation to define AZ protein clusters. Per image, several hundreds to thousands of clusters were analyzed. The x and y coordinates of the center of mass for each cluster were retrieved by Amira software and Euclidean distances between clusters formed by two AZ proteins of interest were determined with a custom-written MATLAB script, previously published in Grauel et al., 2016. Values retrieved for each image were then averaged per mouse. We now show graphs indicating the average number of protein clusters found per each animal analyzed (Figure 2E, Figure 3C,D,I,J, Figure S5C,D,H,J).

Our main goal was to determine if loss of RIM-BP2 impacts the AZ localization of the relevant proteins at different synapse types, looking therefore for relative changes.

2) Differentiating intra-AZ from inter-AZ clusters/Estimating intra-AZ distances for AZ protein clusters:

As correctly pointed out by the reviewers, our gSTED analysis using nearest neighbor detection does a priori not allow us to discriminate between clusters belonging to a single AZ or to nearby AZs. However, the average dimensions of individual AZs have been systematically measured at MF boutons using electron microscopy Rollenhagen et al., 2007. From these data the average AZ diameter is near 390 nm. We therefore first rank in our nearest neighbor analysis the neighbors according to their proximity, and subsequently define protein clusters with an inter-clusters distance dk<390 nm to be putative within individual AZs. This leads to an average of about three Munc13-1 clusters per given MF AZ (Figure 2C). This is slightly below the 5-6 Munc131 nano-assemblies detected per AZ with 3D STORM corresponding to release sites Sakamoto et al., 2018. Thus, we think that the nearest neighbor estimates (k1 type) as retrieved by ourprevious nearest neighbor gSTED analysis is a good representation of intra-AZ neighborhood relations, however, with a contribution of inter-AZ pairs as well (also see below).

To further appreciate these valid concerns, we now include data from previous and additional experiments using postsynaptic marker Homer1 as a reference for intra AZ clusters. As the postsynaptic density region is known to match the extent of the presynaptic active zone (planar membrane contact), by measuring distances between presynaptic clusters adjacent to one postsynaptic Homer1 cluster, we were able to more directly measure intra-AZ distances. We used this approach in particular in immunostaining experiments that measure Munc13-1 to Munc13-1 inter-clusters distances. For both WT and KO MF synapses, the inter-clusters distances retrieved by line profile measurement were somewhat smaller compared to nearest neighbor STED analysis. For example, at control animal MF synapses, the interMunc13-1 cluster distance retrieved with line profile measurements was (165 ± 3 nm, n=6) and with nearest neighbor analysis (213 ± 12 nm, n=6). The difference between the two methods may result from technical reasons or selection bias, but in any case, also line profile measurements showed that loss of RIM-BP2 resulted in a larger distance between two Munc13-1 clusters specifically at MF AZs (Figure 3—figure supplement 3). We are therefore now more confident that RIM-BP2 stabilizes Munc13-1 clusters specifically at MF AZs.

Also, line profile inter-cluster distances between two Cav2.1 clusters opposed to a single Homer1 cluster were comparable between WT and RIM-BP2 KO synapses (Figure 2—figure supplement 1) consistent with our previous nearest neighbor gSTED analysis.

Furthermore, line profile measurement between Munc13-1 to Cav2.1 clusters revealed that Munc13-1 clusters are app. 14 nm further away from Cav2.1 cluster in RIM-BP2 KO MF synapses (86 ± 4, n=6) compared to WT (72 ± 3 nm, n=8; p=0.022311, Mann Whitney U test) (Figure 3—figure supplement 1).

A) The NN-STED analysis is not very meaningful at MF terminals. While NN is insightful for methods that localize individual molecules, it is not for STED, which does not have this capacity. It is uncertain whether any protein cluster is within MF terminals or may be in other synapses around. The nature of biochemical interactions of these proteins suggests that they are intermixed as they all bind to one another, it is not clear that there are separable RIM or CaV2 or Munc13 clusters at distances of 200 nm of each other within an active zone. It is also not clear whether clusters of different proteins belong to the same active zone or even the same synapse. Some of these points are reflected in the data. In Figure 2, it is unclear how RIM, on average, ends up being closer to Homer1 than to CaVs, if the three belong to the same synapse (CaVs sit in the membrane that separates RIM and Homer). Figure 3 claims a reduction in Munc13 levels, but what the author's measure in their analysis is cluster numbers, not levels. It would be much preferable to have a measurement of Munc13 levels within a bouton or within an active zone. This could easily be done in experiments in cultured Dentate Gyrus neuron autapses. The authors should provide either the information on cluster analyzes or find a better way to analyze their STED images.

We thank the reviewers for raising these important points and we appreciate the chance to address them point by point.

1) Meaningfulness of NN gSTED analysis at MF synapses: We agree with the reviewers that our gSTED-based approach cannot localize individual molecules, however our method can detect areas enriched in AZ or postsynaptic proteins at sub-synaptic resolution. We termed these areas clusters, defined based on their fluorescence intensity, as described in our answer to major point 2. We are convinced that the gSTED analysis can inform about relative differences in the nanoscopic protein architecture of AZs based on our findings below.

Differentiating intra-AZ from inter-AZ clusters: As already addressed above, we agree that our nearest neighbor analysis did a priori not allow us to discriminate between clusters belonging to a single AZ or to nearby AZs. We therefore added an additional approach, please see reply to major point 2.

2) Average distance at which RIM1 cluster are found relative to Cav2.1 clusters: Our previous STED analysis at SC synapses showed that RIM1 is found at app. 134 nm from the postsynaptic marker Homer1 Grauel et al., 2016. These values are compatible with published data using STORMDani et al., 2010. Our previous study also showed that the nearest RIM1 cluster in average 185 nm apart from a given Cav2.1 cluster Grauel et al., 2016. The current study shows that the nearest RIM1 cluster is more distant from Cav2.1 clusters (254 nm), indicating structural differences between MF and SC synapses.

3) Munc13-1 levels: to address the reviewers’ question regarding Munc13-1 levels in the RIM-BP2 deficient neurons, we analyzed confocal images for Munc13-1 at MF and CA3-CA1 synapses in situ, acquired in parallel to the gSTED images. Indeed, we observe a significant reduction of Munc13-1 intensity levels specifically at MF synapses compared to CA3-CA1 synapses (Figure 3—figure supplement 3). We included these results in the revised manuscript.

B) On similar lines: One fundamental issue relating the overall conclusion is the number of clusters of each molecules and their spatial separations within the AZ. Given an average AZ area of 0.06 um2, the diameter of such average AZ (assuming disc shape) would be ~280 nm. The authors do not tell the number of clusters for each proteins, but their separation distances are around 260 and 110 nm. The reviewer would like to see the number of clusters per AZ for each presynaptic AZ molecules and their spatial arrangements that is compatible with the measured inter-cluster distances. Without knowing the numbers, the reviewer cannot comprehend whether such cluster separation distances can be consistent with the size of the AZ or not.

We fully concur with the concerns of the reviewers. And as addressed in the reply to major point 2, we now considered AZ size estimates in our calculations. With nearest neighbor gSTED analysis based on EM estimates of MF AZ size, we estimated three Munc13-1 cluster per given MF AZ, slightly below the 5-6 Munc13-1 nanoassemblies found with 3D STORM, corresponding to release sites Sakamoto et al., 2018. We further estimate four RIM-BP2, two Bassoon clusters, three Cav2.1 clusters and one RIM1 cluster per given MF AZ (Figure 2C,H). As second approach, to unequivocally determine intra-AZ distances, we turned to peak-to-peak line measurements of clusters apposed to a single postsynaptic density labeled by Homer1. This analysis indicates that MF AZs display at least two Cav2.1 and two Munc13-1 clusters per AZ, but yielded 20 – 30% shorter distances.

While we fully acknowledge that these measurements are rather proxies for the actual molecular architecture, they revealed whether distinct protein distributions change between wildtype and RIM-BP2 deficient synapses. We detected no change in the distance between two Cav2.1 clusters at MF AZ upon loss of RIM-BP2 (Figure 2—figure supplement 1), as previously shown with our nearest neighbor STED analysis. The inter-cluster distance for Munc13-1 however increased in mossy fiber AZs upon loss of RIM-BP2 (Figure 3—figure supplement 2).

C) How were distances between 'clusters' measured? For example, bassoon seems to form a homogeneous line in Supplementary Figure 1A and RIM-BP and Munc13-1 form some clusters. The authors should demonstrate on the figure how they measured these distances and they should provide more images from which the readers could have an impression of how similar or dissimilar the synapses were with respect to these proteins.

Related to the problem of cluster distance quantification: The authors performed two sets of colocalization experiments: Cav2.1 vs. RIM1 and Munc13-1 vs. RIM BP2. The distances between these clusters were ~ 250 and 170 nm. What is the spatial relationships among them?

In general, we identified AZ protein clusters in deconvolved 2D gSTED images based on an uneven fluorescence signal distribution, upon thresholding and watershed segmentation. Per image, several hundreds to thousands of clusters were analyzed. The x and y coordinates of the center of mass for each cluster were retrieved by Amira software and Euclidean distances between clusters formed by two AZ proteins of interest were determined with a custom-written MATLAB script, previously published in Grauel et al., 2016. Values retrieved for each image were then averaged per mouse. We now show graphs indicating the average number of protein clusters found per each animal analyzed (Figure 2E, Figure 3C,D,I,J, Figure 3—figure supplement 4C,D,H,J).

We now included more detailed information about our nearest neighbor gSTED analysis in the Materials and methods section and cartoons to depict the analysis in each figure.

For each gSTED figure, we now included more insets from the images obtained to better show in details the synapses analyzed.

Regarding the spatial relationship of RIM1 vs. Munc13-1 or RIM-BP, unfortunately we cannot provide estimates. Due to limited availability of the anti RIM1 antibody, whose production has been discontinued by the producing company, we could not perform additional experiments to estimate RIM’s spatial relationship to RIM-BP2 clusters or to Munc13-1 clusters.

3) Another major shortcoming of the manuscript is the lack of detailed demonstration of how RIM-BP2 affects Schaffer collateral (SC) synapses. First, the authors did not perform all localization experiments in SC synapses in parallel with that of mossy fiber synapses. In addition, no functional experiment is presented that would test the prediction of the altered molecular composition of the SC synapses. Please provide the comparative functional data.

We thank the reviewers for pointing this out. In the previous manuscript, we merely compared our data from the MF synapses to previously published results at the SC synapse Grauel et al., 2016. Now, we added gSTED based experiments for RIM1/Cav2.1/Homer1 and Munc13-1/RIM-BP2/Bsn from MF synapses and SC synapses measured from the same brain sections and included these data in our manuscript (subsection “deletion does not alter Ca2+106 -channel localization at the MF synapse”).

Functional electrophysiological experiments at SC synapses in acute brain slices and in hippocampal glutamatergic neuron autaptic culture have been published by us Grauel et al., 2016. Briefly, we could show that at SC synapses loss of RIM-BP2 results in enhanced short term facilitation and that RIM-BP2 fine-tunes Cav2.1 voltage-gated Ca2+-channel localization at SC AZs.

4) A further important addition is to do a better paired-pulse ratio (PPR) analysis in cultured dentate gyrus neurons to assess probability of vesicular release (Pvr). The increased PPR strongly suggest a decrease in Pvr, but the analysis is limited to a single inter-spike-interval. The authors use the sucrose method as a measure of Pvr and argue that Pvr is unchanged, but it remains unclear whether this is a valid way to quantify Pvr at cultured dentate gyrus synapses. A complete analysis of PPRs at cultured dentate gyrus neurons and in hippocampal slices should be performed at various inter-stimulus intervals. This would better connect the slice and culture data sets, and could either support decreased Pvr, or reject this hypothesis. If PPRs indicate decreased Pvr, then this should be better stated in the Title and the Abstract.

Defining whether there is indeed a change in release probability turned out to be not trivial, and we acknowledge in the manuscript, that this remains to be clearly resolved. We applied the two major techniques to test whether release probability is altered upon RIM-BP2 deletion at MF synapses: PPR measurements and estimation of Pvr using hypertonic sucrose. Both methods have their advantages and disadvantages, but have been shown in the past to robustly correlate with each other at small synapses. However, it indeed might be that at MF synapses this relationship is not holding up. Therefore, we performed additional experiments:

a) In a first set of experiments we performed patch-clamp recordings from CA3-pyramidal cells in acute hippocampal slices and stimulated MF EPSCs – while the selectivity of mossy fiber inputs was always tested with DCGIV. In contrast to WT recordings, we rarely observed input of mossy fibers into area CA3 in the RIM-BP2 KO’s, most likely due to the strongly weakened synaptic output. However, this made it also unfeasible to properly quantify synaptic responses, and measures of release probability such as failure rate during minimal stimulation, or paired pulse behavior.

b) As suggested by the reviewer, we further characterized paired-pulse facilitation at RIM-BP2 KO granule autaptic neurons using, in addition to 25 ms, 5 additional inter-stimulus intervals (50ms, 100ms, 150ms, 250ms and 500ms). PPR differences were significant in all but the second longest interstimulus interval in granule autapses compared to WT (Figure 5G).

Together these data support the hypothesis that loss of RIM-BP2 at MF synapses reduces synaptic release probability. However, in contrast to SC synapses, in which we could correlate the decrease in release probability to alterations in Ca2+-channel localization, Cav2.1 localization and abundance is not significantly altered at MF active zones. Nevertheless, here we find that the distance at which Munc13-1 clusters are located relative to Ca2+-channels is significantly increased specifically at MF synapses in RIM-BP2 KO mice. This alteration in the distance between release sites, mapped by Munc13-1, and Ca2+-channels might account for the defect in release probability that we observed at MF terminals in absence of RIM-BP2. In addition, it might be that Munc13-2, since it’s not altered by the deletion of RIM-BP2 at MF terminals, contributes now more to vesicle priming and thus lowers the average release probability respectively Rosenmund et al., 2002. Determination of vesicular release probability using hypertonic sucrose solution however did not show a significant reduction, indicating that the sucrose based method lacks sensitivity to resolve a moderate reduction in vesicular release probability upon loss of RIM-BP2. Alternatively, the loss of RIM-BP2 has a more pronounced effects on processes that affect PPR but less so on Pvr, something that has been previously reported for Rab3 mutants Schluter et al., 2006.

We added the new data to the manuscript and revised the Discussion section about the differential impact of RIMBP2 deletion on short term plasticity and release probability.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Summary:

After careful re-reading of the revised manuscript, all reviewers acknowledge the revision by the authors, the importance of the study and the fact that the study should be published at eLife. However, all reviewers agreed that the details of the image analysis and cluster analysis could be improved.

1) The limitation being that it is unclear whether a cluster belongs to the same active zone or not. Therefore, please further discuss the details of the cluster analysis.

We agree with the reviewers that our nearest neighbor gSTED analysis doesn’t allow us to definitely discriminate between intra- and inter- active zone clusters. We, therefore, added in the Results section and Discussion section the following sentences, to further emphasize this limitation:

Subsection “M-BP2 deletion does not alter Ca2+106 -channel localization at the MF synapse”: “In order to define putative differences in the active zone architecture at MF and CA3-CA1 synapses, we utilized super-resolution STED-microscopy based on detection of major active zone proteins intensities, here referred to as protein clusters. Quantification of the localization of these protein clusters was mainly performed by counting and measuring distances between intensities of these marker proteins.”

Subsection “M-BP2 deletion does not alter Ca2+106 -channel localization at the MF synapse”: “Our gSTED analysis does not allow the differentiation between intra- and inter- active zone protein clusters. However, ultrastructural quantifications of MF active zone size (0.12 µm2)1, are consistent with four RIM-BP2, two Bassoon, and three Munc13-1 clusters per active zone (Figure 2c). Regardless of this semiquantitative analysis, the difference in Munc13-1/RBP cluster distances is indicative for distinct active zone organization between MF and CA3-CA1 synapses.”

Subsection “M-BP2 deletion does not alter Ca2+106 -channel localization at the MF synapse”: “However, it does not allow us to discriminate protein clusters within or between nearby active zones unequivocally.”

Discussion section: “When comparing apparent distances between active zone protein clusters, clusters of the presynaptic scaffold proteins RIM-BP2 and Munc13-1 were found at larger distances at MF synapses as compared to SC synapses. Also, the distance of the closest neighboring cluster of RIM1 to a given Cav2.1 cluster is larger compared to the distance we previously found at SC synapses2. Therefore, our STED analysis suggests that a single active zone may contain more than one protein cluster of key active zone proteins. Some of these key players might have a differential relative localization between each other at MF synapses in comparison to SC synapses. However, further evidence of sub-active zone organization is required to verify this hypothesis. Moreover, more sophisticated methods of defining protein clusters to belong to the same active zone will be helpful in defining the architecture of the active zone of mammalian central synapses.”

2) In this context, please tone down the importance of the cluster analysis in the Abstract.

In the old version of the manuscript, we stated:

“Interestingly, in wild type mossy fiber synapses, the distance between RIM-BP2 clusters and Munc13-1 clusters is larger than in hippocampal pyramidal CA3-CA1 synapses, suggesting that spatial organization may dictate the role a protein plays in synaptic transmission and that differences in active zone architecture is a major determinant factor in the functional diversity of synapses.”

This was changed to:

“Differences in the active zone organization may dictate the role a protein plays in synaptic transmission and that differences in active zone architecture is a major determinant factor in the functional diversity of synapses.”

We hope that the reviewers agree with our changes.

3) Moreover, emphasize the problem with the availability of the RIM antibody that readers understand the limitations.

We now inserted the following sentences in subsection “Immunohistochemistry, time gated STED microscopy and image analysis”:

“Notably, the antibody against RIM1 (RRID: AB_2315284, BD Pharmigen) used in this study is not commercially available anymore. To repeat these results, other RIM1 antibodies need to be utilized and validated beforehand.”

ELife – –

4) Subsection “RIM-BP2 docks synaptic vesicles via the specific recruitment of Munc13-1 at MF synapses”: the docking deficit is ~25%, not 50%, and the text refers to the wrong figure panel.

We changed the percentage accordingly.

https://doi.org/10.7554/eLife.43243.030

Article and author information

Author details

  1. Marisa M Brockmann

    Institut für Neurophysiologie, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing—original draft, Project administration, Writing—review and editing
    Contributed equally with
    Marta Maglione and Claudia G Willmes
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1386-5359

  2. Marta Maglione

    1. Freie Universität Berlin, Institut für Biologie, Berlin, Germany
    2. Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany
    3. NeuroCure Cluster of Excellence, Berlin, Germany
    Contribution
    Conceptualization, Formal analysis, Investigation, Visualization, Writing—original draft, Writing—review and editing
    Contributed equally with
    Marisa M Brockmann and Claudia G Willmes
    Competing interests
    No competing interests declared

  3. Claudia G Willmes

    DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany
    Contribution
    Formal analysis, Investigation
    Contributed equally with
    Marisa M Brockmann and Marta Maglione
    Competing interests
    No competing interests declared

  4. Alexander Stumpf

    Neuroscience Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Investigation, Writing—review and editing
    Competing interests
    No competing interests declared

  5. Boris A Bouazza

    Institut für Neurophysiologie, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  6. Laura M Velasquez

    Neuroscience Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  7. M Katharina Grauel

    Institut für Neurophysiologie, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3542-0606

  8. Prateep Beed

    Neuroscience Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  9. Martin Lehmann

    Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany
    Contribution
    Software
    Competing interests
    No competing interests declared

  10. Niclas Gimber

    Neuroscience Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared

  11. Jan Schmoranzer

    NeuroCure Cluster of Excellence, Berlin, Germany
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared

  12. Stephan J Sigrist

    1. Freie Universität Berlin, Institut für Biologie, Berlin, Germany
    2. NeuroCure Cluster of Excellence, Berlin, Germany
    3. DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany
    Contribution
    Conceptualization, Supervision, Funding acquisition, Investigation, Writing—review and editing
    For correspondence
    stephan.sigrist@fu-berlin.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1698-5815

  13. Christian Rosenmund

    1. Institut für Neurophysiologie, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    2. NeuroCure Cluster of Excellence, Berlin, Germany
    Contribution
    Conceptualization, Supervision, Funding acquisition, Project administration, Writing—review and editing
    For correspondence
    christian.rosenmund@charite.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3905-2444

  14. Dietmar Schmitz

    1. NeuroCure Cluster of Excellence, Berlin, Germany
    2. DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany
    3. Neuroscience Research Center, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing—review and editing
    For correspondence
    Dietmar.Schmitz@charite.de
    Competing interests
    No competing interests declared

Funding

Deutsche Forschungsgemeinschaft (SFB 958 A5)

  • Christian Rosenmund
  • Dietmar Schmitz

Deutsche Forschungsgemeinschaft (SFB 958 A3)

  • Stephan J Sigrist

Deutsche Forschungsgemeinschaft (SFB 958 A6)

  • Stephan J Sigrist

Deutsche Forschungsgemeinschaft (EXC-2049–390688087)

  • Dietmar Schmitz
  • Stephan J Sigrist
  • Christian Rosenmund

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by the Deutsche Forschungsgemeinschaft (Collaborative Research Grant SFB 958 [to DS (A5), SJS (A3, A6), CR (A5)] and Excellence Strategy – EXC-2049–390688087 (to DS, SJS, and CR). We thank Melissa Herman and Gülcin Vardar for providing critical advice for writing the manuscript and Alexander Walter for providing the gSTED analysis script and comments. We thank Berit Söhl-Kielczynski, Anke Schönherr, Susanne Rieckmann und Lisa Züchner for excellent technical support; and Jörg Breustedt for discussions. We thank the Charité viral core facility for virus production and the cellular imaging facility of the Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP) for the use of the gSTED microscope. We thank Anna Fejtova and Eckart Gundelfinger for the RIM-BP2 antibody.

Ethics

Animal experimentation: All animal experiments were approved by the animal welfare committee of Charité Universitaetsmedizin Berlin and the Landesamt für Gesundheit und Soziales Berlin and carried out under the license (Berlin State Government, T0410/12; T0100/03).

Senior Editor

  1. Gary L Westbrook, Oregon Health and Science University, United States

Reviewing Editor

  1. Marlene Bartos, University of Freiburg, Germany

Reviewer

  1. Craig Curtis Garner, German Center for Neurodegenerative Diseases, Germany

Version history

  1. Received: October 30, 2018
  2. Accepted: August 12, 2019
  3. Version of Record published: September 19, 2019 (version 1)

Copyright

© 2019, Brockmann et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,753
    Page views
  • 371
    Downloads
  • 30
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Marisa M Brockmann
  2. Marta Maglione
  3. Claudia G Willmes
  4. Alexander Stumpf
  5. Boris A Bouazza
  6. Laura M Velasquez
  7. M Katharina Grauel
  8. Prateep Beed
  9. Martin Lehmann
  10. Niclas Gimber
  11. Jan Schmoranzer
  12. Stephan J Sigrist
  13. Christian Rosenmund
  14. Dietmar Schmitz
(2019)
RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses
eLife 8:e43243.
https://doi.org/10.7554/eLife.43243

Categories and tags

Research organism

Further reading

    1. Genetics and Genomics
    2. Neuroscience

    Translation of dipeptide repeat proteins in C9ORF72 ALS/FTD through unique and redundant AUG initiation codons

    Yoshifumi Sonobe, Soojin Lee ... Paschalis Kratsios
    Research Article Updated

    A hexanucleotide repeat expansion in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). A hallmark of ALS/FTD pathology is the presence of dipeptide repeat (DPR) proteins, produced from both sense GGGGCC (poly-GA, poly-GP, poly-GR) and antisense CCCCGG (poly-PR, poly-PG, poly-PA) transcripts. Translation of sense DPRs, such as poly-GA and poly-GR, depends on non-canonical (non-AUG) initiation codons. Here, we provide evidence for canonical AUG-dependent translation of two antisense DPRs, poly-PR and poly-PG. A single AUG is required for synthesis of poly-PR, one of the most toxic DPRs. Unexpectedly, we found redundancy between three AUG codons necessary for poly-PG translation. Further, the eukaryotic translation initiation factor 2D (EIF2D), which was previously implicated in sense DPR synthesis, is not required for AUG-dependent poly-PR or poly-PG translation, suggesting that distinct translation initiation factors control DPR synthesis from sense and antisense transcripts. Our findings on DPR synthesis from the C9ORF72 locus may be broadly applicable to many other nucleotide repeat expansion disorders.

    1. Cell Biology
    2. Neuroscience

    Removal of extracellular human amyloid beta aggregates by extracellular proteases in C. elegans

    Elisabeth Jongsma, Anita Goyala ... Collin Yvès Ewald
    Research Article Updated

    The amyloid beta (Aβ) plaques found in Alzheimer’s disease (AD) patients’ brains contain collagens and are embedded extracellularly. Several collagens have been proposed to influence Aβ aggregate formation, yet their role in clearance is unknown. To investigate the potential role of collagens in forming and clearance of extracellular aggregates in vivo, we created a transgenic Caenorhabditis elegans strain that expresses and secretes human Aβ1-42. This secreted Aβ forms aggregates in two distinct places within the extracellular matrix. In a screen for extracellular human Aβ aggregation regulators, we identified different collagens to ameliorate or potentiate Aβ aggregation. We show that a disintegrin and metalloprotease a disintegrin and metalloprotease 2 (ADM-2), an ortholog of ADAM9, reduces the load of extracellular Aβ aggregates. ADM-2 is required and sufficient to remove the extracellular Aβ aggregates. Thus, we provide in vivo evidence of collagens essential for aggregate formation and metalloprotease participating in extracellular Aβ aggregate removal.

    1. Computational and Systems Biology
    2. Neuroscience

    Task-dependent optimal representations for cerebellar learning

    Marjorie Xie, Samuel P Muscinelli ... Ashok Litwin-Kumar
    Research Article Updated

    The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.