Computational complexity of neuronal networks is greatly enhanced by the diversity in synaptic function (Dittman et al., 2000; O'Rourke et al., 2012). It has been known for decades that different types of central neurons form synapses with widely different structures, molecular compositions, and functional properties, resulting in large variations in the amplitude and kinetics of the postsynaptic responses and the type of short- and long-term plasticity. When the mechanisms underlying distinct functions were investigated among synapses made by distinct pre- and postsynaptic cell types (e.g. hippocampal mossy fiber vs. Schaffer collateral vs. calyx of Held vs. cerebellar climbing fiber etc. synapses), most studies converged to the conclusion that different pre- (e.g. different types of Ca channels, Ca sensors) and postsynaptic (e.g. different types of AMPA receptor subunits) molecule isoforms underlie the functional variability (reviewed by Südhof, 2012).

Robust differences in synaptic function were also found when a single presynaptic cell formed synapses on different types of postsynaptic target cells. Such postsynaptic target cell type-dependent variability in vesicle release probability (Pv) and short-term plasticity was identified in cortical and hippocampal networks (Koester and Johnston, 2005; Losonczy et al., 2002; Pouille and Scanziani, 2004; Reyes et al., 1998; Rozov et al., 2001; Scanziani et al., 1998; Thomson, 1997). Studies investigating the underlying mechanisms revealed not only different molecules (e.g. mGluR7, kainate receptors in the AZ and Elfn1 in the postsynaptic density [PSD], Shigemoto et al., 1996; Sylwestrak and Ghosh, 2012), but variable densities of the same molecules were also suggested as key molecular features (Éltes et al., 2017; Rozov et al., 2001).

Probably even more surprising is the large structural and functional diversity of synapses that are established by molecularly identical pre- and postsynaptic neuron types (e.g. synapses among cerebellar molecular layer interneurons [INs], Pulido et al., 2015; among hippocampal CA3, Holderith et al., 2012), suggesting that qualitative molecular differences are unlikely to be responsible for the functional diversity. What could then be responsible for the large diversity in function in such synapses? Pulido et al., 2015 investigated so called simple synapses where the synaptic connection is mediated by a single presynaptic AZ and the opposing PSD. Their results revealed that the number (N) of functional release sites (RSs) varied from 1 to 6 per AZ, and it showed a positive correlation with the quantal size (q). Because in these synapses q is largely determined by the number of postsynaptic GABA_A receptors and because the GABA_A receptor number scales linearly with the synapse area (Nusser et al., 1997), they concluded that the N linearly scales with the synaptic area. Previous results from our laboratory showed that the probability with which release occurs (P_R) from a CA3 PC axon terminal correlates with the size of the synapse. As this probability is the function of both Pv and N [P_R = 1 − (1 − Pv)^N], our results are also consistent with the model that N scales with the synaptic area (Holderith et al., 2012). This view was further supported by a recent paper (Sakamoto et al., 2018), which concluded that in synapses of cultured hippocampal neurons the number of Munc13-1 macromolecular clusters shows a linear correlation with the N and no correlation with Pv. Since Munc13-1 and its invertebrate homologs are essential for docking and priming of synaptic vesicles (Augustin et al., 1999; Imig et al., 2014; Weimer et al., 2006) and the fact that its cluster numbers show tight correlation with N suggests that it is a key molecule of the RSs and can be used as its molecular marker. Thus, the following model emerged: presynaptic AZs are composed from an integer number of uniform, independent RSs, which are built from the same number of identical molecules (molecular units). The more RSs there are, the larger the size of the AZ is, which faces a correspondingly larger PSD containing proportionally more receptors. This model is supported by a number of molecular neuroanatomical studies showing that the number of presynaptic AZ molecules (e.g. Cav2.1, Cav2.2, Rim1/2; Holderith et al., 2012; Kleindienst et al., 2020; Miki et al., 2017) or postsynaptic molecules (e.g. PSD-95, AMPA receptors; Fukazawa and Shigemoto, 2012; Kleindienst et al., 2020) scales linearly with the synapse area. Furthermore, it was also suggested that each RS faces a cluster of postsynaptic AMPA receptors in a so called nanocolumn arrangement (Tang et al., 2016). However, a recent study using superresolution imaging of release from cultured neurons concluded that the RSs are functionally heterogeneous and RSs with high or low Pv are distributed in a nonrandom fashion within individual AZs (Maschi and Klyachko, 2020).

Here, we performed in vitro paired whole-cell recordings followed by quantal analysis to determine the quantal parameters (N, Pv, and q) in synaptic connections between hippocampal CA1 pyramidal cells (PCs) and fast-spiking interneurons (FSINs). Our results demonstrate that the large variability in postsynaptic response amplitude is primarily the consequence of large variations in N. The variability in N is also substantial in individual AZs (N/AZ: 1–17). Multiplexed molecular analysis with STED superresolution microscopy revealed large variability in the Munc13-1 content of AZs that possess the same N, indicating that RSs could be formed by variable number of Munc13-1 molecules. This molecular variability among RSs is supported by our high-resolution electron microscopy replica immunolabeling data, demonstrating highly variable number of gold particles in Munc13-1 clusters in these hippocampal glutamatergic AZs. Whether vesicles that are docked to RSs with different amounts of Munc13-1 have distinct Pv or not remains to be seen.

Data obtained in three independent series of experiments indicate a substantial variability in the molecular content of presynaptic RSs within individual AZs. (1) By determining the N with quantal analysis and subsequently the amounts of Munc13-1 molecules in the functionally characterized AZs, we revealed that AZs with similar Ns have very different amounts of Munc13-1 (Figure 3J). (2) When populations of synapses on FSINs were examined with multiplexed postembedding immunolabeling and STED analysis, the PSD-95 (synapse size)-normalized Munc13-1 immunolabeling showed large variability (Figure 6E). (3) Finally, SDS-FRL, the currently known most sensitive and highest resolution immunolocalization method, demonstrated large variability in the Munc13-1 density in AZs on FSINs and subsequently revealed a synapse size-independent variability in the number of Munc13-1 clusters and in the Munc13-1 content of such clusters (Figure 4J,L).

It is well known that synapses made by molecularly identical presynaptic nerve cells on molecularly identical postsynaptic cells can show large structural and functional variability (reviewed by Pulido and Marty, 2017). In the present study, we examined the connections between hippocampal CA1 PCs and FSINs in adult mice and revealed large variability in uEPSC amplitudes (from 3 to 500 pA, CV = 1) evoked by single PC APs. This large amplitude variability is also present in dendritically unfiltered EPSCs and for both morphologically defined basket and bistratified cells. Quantal analysis demonstrated that variability in N has the largest contribution to the variance in uEPSC amplitudes, which is the consequence of an approximately equal variability in the number of synapses per connection (2.3 ± 1.6, CV = 0.68, from 1 to 7) and the N/AZ (4.9 ± 3.7, CV = 0.75, from 1 to 17). PC to FS basket cell synaptic connections are mediated by a remarkably similar number of synapses in human neocortex (mean = 3.3, range: 1–6; Molnár et al., 2016), cat visual cortex (mean = 3.4, range: 1–7; Buhl et al., 1997), rat neocortex (mean = 2.9, range 1–6; Molnár et al., 2016), and mouse hippocampus (mean = 2.3, range: 1–7; present study). It seems that it is not a unique feature of PC–FSIN connections because a very similar number (mean = 2.8, range: 1–6) was found when CA1 PCs to oriens-lacunosum-moleculare (O-LM) IN connections were examined in juvenile rats (Biró et al., 2005). All data taken together demonstrate that the multi-synapse connection between PCs and GABAergic local circuit INs is an evolutionary conserved feature of cortical networks. As mentioned above, currently it is unknown why PC to IN connections are mediated by multiple (mean of ~3) and variable number (1 – 7) of synaptic contacts.

Unlike the number of synapses per connection, when the N/AZ was compared, a much larger variability and a species-specific difference was found. Molnár et al., 2016 reported that the N/AZ was ~4 times larger in human (~6) compared to rat (1.6) cortical PC–FSIN connections. It is 4.9 for the same connection in adult mouse hippocampus, which is very similar to that found in mouse cultured hippocampal neurons (4.9 in Sakamoto et al., 2018 and 4.2 in Ariel et al., 2012; but 8.7 in Maschi and Klyachko, 2017). The difference in N/AZ between human and rat was accompanied by a larger AZ size in human (0.077 µm²), which is again similar to that obtained in our present study in adult mice (0.071 µm²), indicating that both in human and mice a RS occupies (or needs) approximately the same AZ area. The positive correlation between the docked vesicles and the AZ area (Molnár et al., 2016; Schikorski and Stevens, 1999) is consistent with a model in which the N scales linearly with the AZ area and each independent RS is built up from the same number of molecules (Sakamoto et al., 2018). However, when not only the mean, but the variance in the available data is also considered, a more complex picture emerges. First, there is large variability in the number of docked vesicles in AZs with identical sizes (Figure 3—figure supplement 1 in Molnár et al., 2016), which might reflect variability in RS density, but an incomplete docking site/RS occupancy cannot be excluded. Such incomplete RS occupancy cannot explain our data showing that AZs with the same amount of PSD-95 (same size) have >3 fold variability in N. Thus, it seems that variability in the docking site occupancy might not be the main source of variability, but the actual RS density seem to be variable. A similar large variability is present in the data of Figure 3c in Sakamoto et al., 2018 in the correlation between the readily releasable pool size (N_RRP) and the number of labeled Munc13-1 molecules. The almost identical number of RSs and N_RRP indicates a docking site occupancy close to one in their cultured hippocampal neurons again arguing for the variability in either the RS density or in the number of Munc13-1 molecules per RS. Our high-resolution SDS-FRL experiments provide direct evidence for both: substantial variability in the Munc13-1 cluster (i.e. RS) density in AZs and in the number of Munc13-1 molecules per cluster (Figure 4H,L).

One consequence of the variable number of docked vesicles or RS density is that the inter RS distance varies substantially in AZs of identical sizes. One possible consequence of that is that the RSs might not function independently when they are close enough to ‘see’ substantial amounts of Ca²⁺ from the neighboring RSs. Our data, showing that the average Pv of the RSs does not depend on the N/AZ (Figure 2J), together with that of Sakamoto et al., 2018, demonstrating that Pv does not depend on the N_RRP, strongly indicate that the average Pv does not depend on the size of AZ. A pervious study from our laboratory (Holderith et al., 2012) described that the probability with which release occurs at hippocampal synapses (P_R) depends on the AZ size. We would like to stress that this probability (P_R) is the function of both the Pv and N [P_R = 1-(1-Pv)^N]; therefore, the synapse size-dependent increase in N fully explains our previous and current results.

What might be the consequence of the variable amounts of Munc13-1 in RSs? Munc13-1 is an evolutionally conserved presynaptic protein that is essential for docking and priming vesicles for release (Augustin et al., 1999; Betz et al., 2001; Brockmann et al., 2020; Imig et al., 2014; Jahn and Fasshauer, 2012; Ma et al., 2011; Varoqueaux et al., 2002); therefore, it can be hypothesized that the amount of this molecule might have an effect on the docking site occupancy or the priming state of the vesicles. MPFA only allows the determination of Pv, a probability that depends on the probability of the RS being occupied (P_occ) and on the probability of a docked vesicle being released (P_succ; Neher, 2017). Two lines of evidence indicate that P_occ is high at neocortical/hippocampal glutamatergic synapses. As mentioned above, Sakamoto et al., 2018 came to this conclusion from the similar N_RRP and Molnár et al., 2016 examined the number of docked vesicles at cortical PC–FSIN synapses and determined N, and found rather similar values for both human and rat synapses, arguing for a P_occ of ~0.8 that is similar to that found at the Calyx of Held (Neher, 2010), but larger than at cerebellar IN synapses (Pulido et al., 2015). Thus, it seems that variability in P_occ might not be the major consequence of the variable amounts of Munc13-1 per RS, indicating that the priming state of the vesicles and therefore the P_succ might be affected. Heterogeneity in the Pv for different vesicles has been demonstrated at the AZs of the Calyx of Held (reviewed by Neher, 2017). Here, approximately half of the vesicles have high and the other halves have low Pv. Furthermore, there is also data indicating further heterogeneity in the Pv of the fast releasing (high Pv) vesicles in the Calyx (normally primed and superprimed vesicles; Taschenberger et al., 2016 and in hippocampal synapses as well Hanse and Gustafsson, 2001; Schlüter et al., 2006). Whether such high- and low-Pv vesicles are intermingled within individual AZs or are segregated to distinct AZs is unknown. It is just as unknown whether the normally and superprimed vesicles need different amounts of Munc13-1 or not. It is noteworthy that the priming efficacy of Munc13-1 depends on its interaction with RIM and RIM binding protein (Brockmann et al., 2020) therefore predicting the functional consequence of the different amounts of Munc13-1 per RS might require the determination of these molecules in individual Munc13-1 clusters. A recent study using superresolution imaging of vesicle release from cultured hippocampal neurons provided strong evidence for the heterogeneity in Pv among RSs within individual AZs. Maschi and Klyachko, 2020 demonstrated that the Pv of centrally located RSs is higher and participate more frequently in multivesicular release (MVR) than those that are located at the periphery of the AZs. These data taken together indicate substantial variability in Pv among RSs, which is more likely to be the consequence of variable P_succ, the relationship of which to the amounts of Munc13-1 molecules remains to be seen.

A recent study applied superresolution light microscopy to examine the spatial relationship between pre- and postsynaptic molecules and came to the conclusion that key molecules are arranged in transsynaptic nanocolumns (Tang et al., 2016). Specifically, the number of RIM1 clusters in the AZ was similar to that of PSD-95 in the PSD and they face one another in a remarkable fashion. Other presynaptic molecules such as Munc13-1 and bassoon were also clustered, but their numbers were higher and lower, respectively than that of PSD-95, slightly complicating the picture. Our present data and that of Rebola et al., 2019 showing clustering of Munc13-1 in the AZs is consistent with such a model. However, our data demonstrating virtually zero synapse size-independent variability in the amounts of PSD-95 molecules, but large variability in the Munc13-1 seems to be inconsistent with such a model. In addition, the distribution of our PSD-95 labeling does not indicate strong intra synapse clustering either. A more direct evidence against the nanocolumn organization as a universal feature of all glutamatergic synapses comes from a previous study form our laboratory, demonstrating that postsynaptic AMPA receptors do not show clustered sub-synaptic distribution in cerebellar and hippocampal glutamatergic synapses on GABAergic INs (Szoboszlay et al., 2017). All these data taken together indicates that the nanocolumn arrangement of pre- and postsynaptic key signaling molecules is not a universal feature of all glutamatergic synapses.

Our results are also compatible with the concept that individual cortical synapses release more than a single vesicle from an AZ upon the arrival of a single AP (called MVR; Biró et al., 2006; Christie, 2006; Maschi and Klyachko, 2020; Pulido et al., 2015; Rudolph et al., 2015; Wadiche and Jahr, 2001). The occurrence of MVR is the function of N/AZ and Pv. All available data indicate that cortical/hippocampal excitatory and inhibitory synaptic AZs contain multiple RSs, the number of which positively correlates with the size of the AZ, fulfilling one essential requirement of MVR. The average Pv, however, is much more heterogeneous. The most compelling evidence for variable Pv in distinct boutons is the postsynaptic target cell type-dependent variability in Pv and short-term plasticity (Éltes et al., 2017; Koester and Johnston, 2005; Losonczy et al., 2002; Pouille and Scanziani, 2004; Reyes et al., 1998; Rozov et al., 2001; Scanziani et al., 1998; Thomson, 1997). A previous study from our laboratory demonstrated that Pv at hippocampal CA1 PC to O-LM cell synapses is so low that the occurrence of MVR is negligible under physiological conditions (Biró et al., 2005). However, the Pv at PC–FSIN synapses is an order of magnitude higher (~0.4) than that at PC–O-LM synapses and given an average of five RSs per AZ, the probability of MVR is around 70%. We would like to emphasize that Pv at CA3 to CA1 PC synapses is probably in between these values, indicating that the occurrence of MVR is much less prominent. The degree of postsynaptic receptor occupancy is a key issue when the functional consequence of MVR is considered. If the occupancy is high (e.g. cerebellar climbing fiber to Purkinje cell synapses; Harrison and Jahr, 2003 or at cerebellar molecular layer IN synapses, Auger et al., 1998; Nusser et al., 1997), the effect of simultaneously released multiple vesicles is small (not necessarily zero, because of the effect on the time course of the postsynaptic response; Rudolph et al., 2011). However, increasing evidence indicates that receptor occupancy is relatively low at most central glutamatergic synapses, allowing the postsynaptic cell to detect the number of simultaneously released vesicles within a single synapse either linearly or sublinearly. Our result, showing no correlation between the q and N/AZ (Figure 2J), is also consistent with this. Such MVR operation of synapses by increasing the reliability of transmission and reducing stochastic trial-to-trial variability might provide an important circuit element with which perisomatic GABAergic inhibition is recruited reliably by an active ensemble of PCs.

Source data have been provided for all figures.

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Author details

1. Maria Rita Karlocai

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology

   Competing interests

   No competing interests declared

2. Judit Heredi

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Data curation, Formal analysis, Methodology

   Competing interests

   No competing interests declared

3. Tünde Benedek

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

4. Noemi Holderith

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Conceptualization, Formal analysis

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0024-3980

5. Andrea Lorincz

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2430-5290

6. Zoltan Nusser

   Laboratory of Cellular Neurophysiology, Institute of Experimental Medicine, Budapest, Hungary

   Contribution

   Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Writing - original draft, Writing - review and editing

   For correspondence

   nusser.zoltan@koki.mta.hu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7004-4111

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