During brain development, synapse assembly and maturation are critical processes involving several families of adhesion molecules, among which the neurexin-neuroligin complex has been one of the most extensively studied (Bemben et al., 2015b; Chanda et al., 2017; Letellier et al., 2018; Südhof, 2017; Wu et al., 2019). Neuroligins (NLGNs) are post-synaptic proteins that comprise four members in rodents (NLGN1-4), NLGN1 being primarily localized at excitatory synapses, NLGN2 and NLGN4 at inhibitory synapses, and NLGN3 at both types of synapses (Budreck and Scheiffele, 2007; Varoqueaux et al., 2004). At the structural level, NLGNs form both homo- and hetero-dimers through cis-interactions between their acetylcholinesterase (AchE)-like domains (Araç et al., 2007; Chen et al., 2008; Dean et al., 2003; Fabrichny et al., 2007; Poulopoulos et al., 2012). NLGNs also contain a stalk region that can be cleaved by proteases (Peixoto et al., 2012; Suzuki et al., 2012), a single pass transmembrane domain, and a conserved intracellular tail whose binding to post-synaptic scaffolding molecules can be modulated by phosphorylation and thereby influence AMPA receptor (AMPAR) recruitment (Antonelli et al., 2014; Bemben et al., 2014; Bemben et al., 2015a; Giannone et al., 2013; Letellier et al., 2020; Letellier et al., 2018; Poulopoulos et al., 2009). Post-synaptic NLGNs bind pre-synaptic neurexins (NRXNs) through extracellular interactions, thus making a bridge between sub-micron adhesive modules across the synaptic cleft that precisely position AMPARs (Chamma et al., 2016a; Haas et al., 2018; Trotter et al., 2019).

Apart from NRXNs, few direct NLGN binding partners have been identified (Südhof, 2017). Recently, MAM-domain GPI-anchored molecules (MDGAs) were reported to bind in cis to NLGNs with high affinity and compete with their binding to NRXNs (Connor et al., 2019). In the co-culture assay, the expression of MDGAs together with NLGNs in heterologous cells impairs the synapse-inducing activity of NLGNs on contacting axons (Elegheert et al., 2017; Lee et al., 2013; Pettem et al., 2013). Crystal structures of MDGA-NLGN complexes revealed that MDGAs bind through their first Ig1-Ig2 domains to the two lobes of the NLGN extracellular dimer, at sites which overlap with the NRXN binding interface (Elegheert et al., 2017; Gangwar et al., 2017; Kim et al., 2017). Manipulations of MDGA1 protein levels by over-expression (OE), knock-down (KD), or knock-out (KO) in neurons have led to the common view that MDGA1 selectively inhibits inhibitory synapse formation by primarily repressing NLGN2-NRXN interactions (Connor et al., 2017; Lee et al., 2013; Loh et al., 2016; Pettem et al., 2013). Similar studies performed on MDGA2 have led to more debated results, i.e. some reports showing that MDGA2 KO specifically inhibits excitatory synapse formation in vivo (Connor et al., 2016), while others showing no effect of MDGA2 KD on either excitatory or inhibitory synapses in culture (Loh et al., 2016).

Notwithstanding the foregoing, there are still a number of critical questions that need to be answered in order to get a more complete picture of the role of MDGAs in synapse differentiation and function (Connor et al., 2019; Thoumine and Marchot, 2017). 1 / What is the surface dynamics and nanoscale localization of endogenous MDGAs at the neuronal membrane? Indeed, in the absence of highly specific and efficient antibodies to MDGAs allowing reliable immunostaining in tissue, over-expression approaches have yielded contrasting results about the presence of MDGA1 and MDGA2 at excitatory versus inhibitory synapses (Loh et al., 2016; Pettem et al., 2013). Given the absence of an intracellular domain with potential synaptic retention motifs, MDGAs are in fact expected to display fast membrane diffusion and not accumulate at synapses. 2 / Considering that the binding of MDGAs and NRXNs to NLGNs is mutually exclusive, what is the effect of MDGAs on the dynamic distribution of NLGN in dendrites and on the NLGN-dependent phosphotyrosine signaling pathway known to regulate post-synaptic differentiation (Giannone et al., 2013; Letellier et al., 2018)? 3 / Consequently, what is the impact of MDGAs on AMPAR surface dynamics and synaptic function, which were shown to be tightly regulated by NLGN1 (Czöndör et al., 2013; Haas et al., 2018; Letellier et al., 2020; Mondin et al., 2011)?

To address those questions, we examined the surface localization and dynamics of MDGAs, using both custom-made antibodies to endogenous MDGA1 as well as replacement strategies with recombinant MDGAs bearing small tags and labelled with monomeric fluorescent probes. Using a combination of single-molecule imaging and electrophysiology, we also assessed the effects of single-cell MDGA knock-down or knock-out on NLGN1 and AMPAR membrane diffusion and localization in relation to synapse maturation, as well as on synaptic transmission. Finally, we examined the impact of MDGA knock-down on endogenous NLGN phosphotyrosine levels by biochemistry. Together, our data indicate that MDGAs are highly mobile and homogeneously distributed molecules, that alter both NLGN1 and AMPAR dynamics, localization, and function, thereby significantly delaying the differentiation of excitatory post-synapses.

In this study, we characterized the membrane localization of MDGAs and their role on the dynamics and signaling of their direct binding partner, NLGN1, as well as associated effects on synaptic differentiation and the recruitment of AMPARs. We demonstrate that both MDGA1 and MDGA2 are essentially non-synaptically enriched molecules that exhibit fast diffusion in the dendritic membrane. Moreover, the knock-down of MDGAs selectively increases excitatory synapse density and as a consequence reduces the surface mobility of both NLGN1 and AMPARs, increases AMPAR-mediated mEPSC frequency and evoked EPSC amplitude, as well as NLGN1 phosphosignaling. Thus, by shielding a fraction of NLGN1 from binding to pre-synaptic NRXNs, MDGAs negatively regulates NLGN function in excitatory synaptic differentiation (Figure 10).

Figure 10

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We first examined the localization of MDGAs in hippocampal tissue and dissociated cultures. The generation of specific antibodies allowed us to examine the distribution of native MDGA1, which showed strong expression levels in the neuropil of the CA region of the hippocampus, confirming previously shown results of in situ hybridization of MDGA1 mRNAs and staining of β-galactosidase activity expressed from the Mdga1 locus (Connor et al., 2017; Connor et al., 2016; Lee et al., 2013). MDGA1 immunostaining in dissociated cultures at DIV 14 showed that a large fraction of excitatory synapses did not contain MDGA1. Recombinant MDGA1 and MDGA2 expressed by rescuing endogenous MDGA levels also showed no preferential retention at Homer1c-positive puncta, in contrast with the positive controls NLGN1 and LRRTM2 labeled similarly and showing strong post-synaptic accumulation, as previously described (Chamma et al., 2016a). Previous studies also reported a small colocalization extent of either YFP-MDGA1 or HRP-MDGA2 with excitatory synaptic markers (Loh et al., 2016; Pettem et al., 2013). Our results show that individual MDGAs often localized as transient sub-micron clusters at the periphery of Homer1c puncta, representing the confinement area of a small number of labeled molecules. The nature of these domains is unclear, but might represent a transition zone where NLGN1 could switch between MDGA-bound and NRXN-bound states, with the potential existence of mixed NLGN1 dimers that would exhibit specific mobility properties. In any case, the sum of this MDGA-rich peri-synaptic compartment plus the diffusive pool of MDGAs in synapses might represent enough material to be detected in synaptosomes (this study) and in the synaptic cleft proteome (Loh et al., 2016). When sampled at saturating labeling density using dSTORM, MDGAs showed a rather diffuse localization in the shaft and at synapses both at DIV 10 and 14, with modest synaptic enrichment as the negative control GFP-GPI. As compared to uPAINT, which gives information on the membrane dynamics of a subset of sparsely labeled molecules, dSTORM performed after saturating live labeling provides a snapshot of the whole population of MDGAs that integrates over time many transient confinement areas into a single 2D projection image. Thus the localization of molecules observed in dSTORM seems naturally more homogeneous, as previously reported for NLGN1 (Chamma et al., 2016a).

In addition, AP-MDGA1 and AP-MDGA2 exhibited fast membrane diffusion throughout dendrites, even within post-synaptic sites, indicating no particular molecular retention at synapses. These observations are compatible with the fact that MDGAs lack an intracellular C-terminal domain such as those present in NLGN1 or AMPAR auxiliary subunits, which bind PDZ domain-containing scaffolding proteins that stabilize them at synapses (Bats et al., 2007; Irie et al., 1997; Mondin et al., 2011). A mild confinement of MDGAs outside synapses was observed upon neuronal maturation, which might be due to the fact that a fraction of MDGAs bind to extra-synaptic NLGN clusters (Gerrow et al., 2006) or to another unknown protein, e.g. through their Ig4-6 domains (Lee et al., 2013). These domains might also be due to interactions of the GPI anchor of MDGAs to the lipid microenvironment present in some membrane microdomains such as lipid rafts (Díaz-López et al., 2005; Renner et al., 2009). By comparing side by side the distributions of diffusion coefficients for MDGAs and NLGN1, we estimate that around 12% of the highly mobile extra-synaptic MDGAs are not bound to NLGN1, otherwise MDGAs would naturally adopt the slower diffusion of NLGN1. Furthermore, the fact that MDGAs do not accumulate at synapses like NLGN1 over neuronal development (from DIV 10–14) suggests that synaptic NLGN1 is not bound to MDGAs, but instead to NRXNs which display high local concentration at pre-synapses (Chamma et al., 2016a; Chamma et al., 2016b). Thus, by preventing dendritic NLGN1 from aberrantly binding to the fraction of freely-diffusing NRXNs at the surface of contacting axons (Chamma et al., 2016a; Neupert et al., 2015), native MDGAs seem to protect neurons from forming synapses too quickly.

Using either previously reported shRNAs or newly generated CRIPSR/Cas9 constructs, we showed that MDGA2 delays excitatory synaptic development and AMPAR-dependent transmission, consistent with the in vivo KO of Mdga2 (Connor et al., 2016). These effects were accompanied by a global decrease of NLGN1 diffusion, supporting the idea that by losing its MDGA partner, NLGN1 is more available to bind axonal NRXNs and thereby accelerates synapse formation. Indeed, the effects of MDGA2 KD and KO were more prominent at DIV 10 during the active phase of synaptogenesis, and barely detectable at DIV 14, in agreement with the lack of effect of shMDGA2 previously seen on excitatory synapse density in DIV 15 neurons (Loh et al., 2016). Upon MDGA2 knock-down, there was no significant increase in the synaptic enrichment of either NRXN1β or NLGN1, suggesting that synapses can be newly assembled using a fixed number of those trans-synaptic adhesion molecules. We found more contrasted results with MDGA1, that is the CRISPR/Cas9 strategy significantly increased excitatory post-synaptic density and AMPAR-mediated mEPSC frequency at DIV 10 in dissociated neurons, as well as evoked AMPAR-mediated EPSCs in organotypic slices, while shRNA to MDGA1 had little effect at both DIV 10 and DIV 14, in agreement with previous reports (Pettem et al., 2013). The discrepancy might be due to the fact that CRISPR/Cas9 represses MDGA1 expression more strongly than shMDGA1. Indeed, in previous studies, effects of MDGAs on excitatory and inhibitory synapse development were seen only when both MDGA1 and MDGA2 were knocked down (Lee et al., 2013; Loh et al., 2016), suggesting that MDGA1 and MDGA2 might compensate for each other’s loss such that the important parameter in these experiments is the overall MDGA level. The selective increase in inhibitory - but not excitatory - synapses in hippocampal CA1 neurons of full Mdga1 KO mice (Connor et al., 2017) might come from the fact that MDGA1 is silenced throughout the whole animal lifetime, which might lead to compensatory effects. Furthermore, MDGA1 knock-out affects all cell types, including both pyramidal neurons and astrocytes that also express MDGA1 and NLGNs (Stogsdill et al., 2017), which might overall cause mixed effects on hippocampal circuitry. A difference in the results obtained by global gene knock-out in mice and sparse single-neuron silencing was also seen for NLGN1 (Chih et al., 2005; Varoqueaux et al., 2006), suggesting that adhesion-dependent competition between neurons regulates synaptogenesis (Kwon et al., 2012), although sparsely knocking out NLGN1 did not reduce synapse number in another study (Chanda et al., 2017). Strikingly, the phenotypes we saw with single cell MDGA2 KO (e.g. increases in post-synapse numbers and AMPAR-mediated mEPSC frequency in dissociated neurons) resembles the ones we previously observed by over-expressing NLGN1, thereby reinforcing the view that neurons compete for synapse formation through NRXN-NLGN adhesion. MDGA1 KO had more subtle effects, that is it significantly increased AMPAR-mediated mEPSC frequency but not the density of VGlut1 or GluA1 puncta, which might be due to the fact that electrophysiology is a more sensitive technique than immunostaining to detect AMPAR-dependent synaptic changes (Letellier et al., 2018). In any case, crystal structures and affinity measurements support the concept of a stable MDGA1-NLGN1 complex (Elegheert et al., 2017; Gangwar et al., 2017; Kim et al., 2017), which should be compatible with the fact that endogenous MDGA1 can interact with NLGN1 as strongly as MDGA2 to impair excitatory synapse formation.

We also demonstrated a selective increase in the phosphotyrosine level of NLGNs upon MDGA2 knock-down. This observation relates to our previous findings that NLGN1 can be phosphorylated at a unique intracellular tyrosine residue (Y782), and that the NLGN1 phosphotyrosine level regulates the assembly of excitatory post-synaptic scaffolds in a NRXN-dependent fashion (Giannone et al., 2013). Moreover, using either the expression of NLGN1 point mutants or the optogenetic stimulation of endogenous NLGN1 phosphorylation, we showed that a high NLGN1 phosphotyrosine level is associated with the selective increase in excitatory synapse number and AMPAR-mediated synaptic transmission (Letellier et al., 2020; Letellier et al., 2018). Strikingly, single-cell MDGA KO in CA1 neurons selectively enhanced AMPAR- (but not NMDAR-) mediated synaptic transmission, further implicating NLGN in the recruitment of AMPARs at nascent synapses. We thus propose the model that by occupying NLGN1, MDGAs inhibit the NRXN-induced phosphotyrosine signaling pathway associated with NLGN1 and thereby delay the assembly of functional excitatory synapses containing AMPARs. In this context, we were surprised not to observe any impact of MDGA KD on the global diffusion or pre-synaptic accumulation of GFP-NRXN1β in axons contacting neurons expressing shMDGA2, but these effects might have been obscured by the limited number of contacts between these cells or by NRXN1β over-expression. Future single-molecule tracking experiments on NRXN1-α or -β expressed at endogenous levels may allow one to clarify this issue (Klatt et al., 2021; Neupert et al., 2015). The enhancement of NLGN tyrosine phosphorylation caused by MDGA2 KD might be linked to the increased number of synapses, leading to enhanced local concentration of receptor tyrosine kinases such as Trk family members that are able to phosphorylate native NLGNs (Letellier et al., 2018). Since NLGN3 can also be tyrosine phosphorylated in neurons (Letellier et al., 2018), a contribution of NLGN3 to the increase in phosphotyrosine level seen upon MDGA2 KD is possible given that we used a pan NLGN antibody to reach efficient immunoprecipitation. However, the fact that MDGA binds 10-fold more weakly to NLGN3 than to NLGN1 in vitro (Elegheert et al., 2017), and that the effects of NLGN tyrosine phosphorylation on post-synaptic differentiation are not seen in cultures from NLGN1 KO mice (Letellier et al., 2020) suggest that NLGN3 might only play a minor role in this process.

The decrease in global AMPAR diffusion observed upon MDGA2 knock-down can be linked to the parallel increase in the number of synaptic puncta. Indeed, a similar decrease in AMPAR diffusion was seen across neuronal development in culture or upon the over-expression of NLGN1, which both enhance the number of post-synapses that act as trapping elements for surface diffusing AMPARs (Czöndör et al., 2012; Mondin et al., 2011). Upon MDGA2 knock-down, a transient immobilization of surface-diffusing AMPARs is expected to occur at newly formed synapses enriched in NLGN1, resembling what was previously observed at micro-patterned dots coated with NRXN1β-Fc (Czöndör et al., 2013). Interestingly, the actual content of AMPARs per post-synapse did not seem to be modified by MDGA KO in dissociated neurons, since both the synaptic AMPAR enrichment and the amplitude of AMPAR-mediated mEPSCs remained similar to control conditions. However, the density of synaptic puncta as well as the frequency of AMPAR-mediated mEPSCs were significantly enhanced by MDGA KO, suggesting that the new synapses that had appeared contained functional AMPARs. This situation is similar to NLGN1 over-expression that increases the number of synapses and the frequency, but not the amplitude, of AMPAR-mediated mEPSCs (Letellier et al., 2018; Levinson et al., 2005). In both cases (MDGA knock-down or NLGN overexpression), AMPARs seem to be inserted in novel synapses as individual units or modules, most likely influenced by the presence of NLGN1 (Haas et al., 2018; Hruska et al., 2018; MacGillavry et al., 2013; Nair et al., 2013). In organotypic slices, MDGA KO selectively enhanced the AMPA/NMDA ratio in CA1 neurons but did not affect NMDAR-mediated EPSCs, indicating no net change in synapse number but instead an unsilencing mechanism (Kerchner and Nicoll, 2008). This process might also occur in dissociated neurons where the increase in the frequency of AMPAR-mediated mEPSCs upon MDGA KD (3-fold) was much larger than the enhancement in synapse number (50%). In any case, the robust recruitment of AMPARs through synaptogenic and/or unsilencing mechanisms ressembles the effects previously observed upon direct manipulation of NLGN1 expression or signaling (Letellier et al., 2020; Letellier et al., 2018; Mondin et al., 2011), suggesting that MDGAs act through a regulation of NLGN1 function.

Given the strong effects caused by MDGA loss-of-function on synaptic differentiation, the next challenge would be to determine which biological processes regulate endogenous MDGA levels in specific neuron types across development. One interesting factor might be constitutive neuronal activity that can influence synaptic protein expression levels, for example by modulating microRNAs (Dubes et al., 2019; Letellier et al., 2014). Indeed, MDGA1 transcripts were recently found to be regulated in response to chronic synaptic activity blockade (Silva et al., 2019). Moreover, the action of MDGAs might be finely tuned by other proteins associated to the NRXN-NLGN trans-synaptic complex, including hevin and SPARC that are secreted by astrocytes (Fan et al., 2021). Interestingly, the presence of NLGNs in astrocytes offers an additional level of regulation of synapse development through such a network of proteins (Stogsdill et al., 2017). Finally, genetic mutations identified in patients with autism and leading to alterations in MDGA levels (Bucan et al., 2009), are expected to cause profound changes in synapse differentiation such as the ones shown here.

All data generated or analysed during this study are included in the manuscript and supporting file; source data files are provided.

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Author details

1. Andrea Toledo

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

2. Mathieu Letellier

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – review and editing

   Contributed equally with

   Giorgia Bimbi

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4008-298X

3. Giorgia Bimbi

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Data curation, Formal analysis, Investigation, Methodology, Writing – review and editing

   Contributed equally with

   Mathieu Letellier

   Competing interests

   No competing interests declared

4. Béatrice Tessier

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Data curation, Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

5. Sophie Daburon

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Conceptualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

6. Alexandre Favereaux

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

7. Ingrid Chamma

   University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

8. Kristel Vennekens

   VIB Center for Brain & Disease Research and KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium

   Contribution

   Methodology

   Competing interests

   No competing interests declared

9. Jeroen Vanderlinden

   VIB Center for Brain & Disease Research and KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

10. Matthieu Sainlos

    University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

    Contribution

    Conceptualization, Methodology, Resources, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5465-5641

11. Joris de Wit

    VIB Center for Brain & Disease Research and KU Leuven, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium

    Contribution

    Conceptualization, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

12. Daniel Choquet

    1. University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France
    2. University of Bordeaux, CNRS UAR 3420, INSERM, Bordeaux Imaging Center, Bordeaux, France

    Contribution

    Conceptualization, Project administration, Resources, Supervision, Writing – review and editing

    Contributed equally with

    Olivier Thoumine

    For correspondence

    daniel.choquet@u-bordeaux.fr

    Competing interests

    No competing interests declared

13. Olivier Thoumine

    University of Bordeaux, CNRS UMR 5297, Interdisciplinary Institute for Neuroscience, Bordeaux, France

    Contribution

    Conceptualization, Methodology, Project administration, Resources, Supervision, Methodology, Writing – review and editing

    Contributed equally with

    Daniel Choquet

    For correspondence

    olivier.thoumine@u-bordeaux.fr

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8041-1349

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