The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression

  1. Martin Baccino-Calace
  2. Katharina Schmidt
  3. Martin Müller  Is a corresponding author
  1. Department of Molecular Life Sciences, University of Zurich, Switzerland
  2. Zurich Ph.D. Program in Molecular Life Sciences, Switzerland
  3. Neuroscience Center Zurich, University of Zurich/ETH Zurich, Switzerland

Abstract

Synaptic proteins and synaptic transmission are under homeostatic control, but the relationship between these two processes remains enigmatic. Here, we systematically investigated the role of E3 ubiquitin ligases, key regulators of protein degradation-mediated proteostasis, in presynaptic homeostatic plasticity (PHP). An electrophysiology-based genetic screen of 157 E3 ligase-encoding genes at the Drosophila neuromuscular junction identified thin, an ortholog of human tripartite motif-containing 32 (TRIM32), a gene implicated in several neurological disorders, including autism spectrum disorder and schizophrenia. We demonstrate that thin functions presynaptically during rapid and sustained PHP. Presynaptic thin negatively regulates neurotransmitter release under baseline conditions by limiting the number of release-ready vesicles, largely independent of gross morphological defects. We provide genetic evidence that thin controls release through dysbindin, a schizophrenia-susceptibility gene required for PHP. Thin and Dysbindin localize in proximity within presynaptic boutons, and Thin degrades Dysbindin in vitro. Thus, the E3 ligase Thin links protein degradation-dependent proteostasis of Dysbindin to homeostatic regulation of neurotransmitter release.

Editor's evaluation

The paper focuses on presynaptic homeostatic plasticity (PHP) at the glutamatergic larval Drosophila neuromuscular synapse. In this facet of synaptic plasticity, the presynapse increases neurotransmitter release to compensate for diminished postsynaptic sensitivity. To study functional pathways and identify new molecular components of PHP, the authors carried out an electrophysiology-based genetic screen of E3 ubiquitin ligases – key regulators of protein function and degradation pathway and this screen, which forms the backbone of the paper, generated an extensive dataset encompassing 180 genotypes. In follow-up studies, the authors find that the E3 ligase Thin suppresses glutamate release, likely by targeting and downregulating Dysbindin, a transmitter-release-promoting presynaptic protein and based on the experimental data, a model is put forward according to which PHP arises by relieving Dysbindin of Thin-dependent ubiquitination and degradation. This is a strong paper that adds a highly interesting feature to the understanding of the molecular mechanisms that control synaptic strength.

https://doi.org/10.7554/eLife.71437.sa0

Introduction

Nervous system function is remarkably robust despite continuous turnover of the proteins determining neural function. Work in nervous systems of various species has established that evolutionarily conserved homeostatic signaling systems maintain neural activity within adaptive ranges (Marder and Goaillard, 2006; Turrigiano, 2008; Delvendahl and Müller, 2019b). Chemical synapses evolved mechanisms that compensate for neural activity perturbations through homeostatic regulation of neurotransmitter release (‘presynaptic homeostatic plasticity’, PHP) (Petersen et al., 1997; Frank et al., 2006; Delvendahl and Müller, 2019b), or neurotransmitter receptors (synaptic scaling) (Turrigiano et al., 1998). Several studies have established links between homeostatic control of synaptic transmission and neurological disorders, such as autism spectrum disorder (Mullins et al., 2016), schizophrenia (Wondolowski and Dickman, 2013), or amyotrophic lateral sclerosis (Perry et al., 2017; Orr et al., 2020).

Synaptic proteins are continuously synthesized and degraded, resulting in half-lives ranging from hours to months (Cohen et al., 2013; Fornasiero et al., 2018). The ubiquitin–proteasome system (UPS) is a major protein degradation pathway that controls protein homeostasis, or proteostasis. E3 ubiquitin ligases confer specificity to the UPS by catalyzing the ubiquitination of specific target proteins, thereby regulating their function or targeting them for proteasomal degradation (Zheng and Shabek, 2017). Synaptic proteostasis, and E3 ligases in particular, have been implicated in various neurological disorders (George et al., 2018). However, our understanding of the role of E3 ligases in the regulation of synaptic transmission is very limited. While several E3 ligases have been linked to postsynaptic forms of synaptic plasticity (Hegde, 2010), only three E3 ligases, Scrapper (Yao et al., 2007), Highwire (Russo et al., 2019), and Ariadne-1 (Ramírez et al., 2021) have been implicated in the regulation of presynaptic function. Moreover, a systematic investigation of E3 ligase function in the context of synaptic transmission is lacking.

PHP stabilizes synaptic efficacy in response to neurotransmitter receptor perturbation at neuromuscular junctions (NMJs) of Drosophila melanogaster (Petersen et al., 1997; Frank et al., 2006; Delvendahl and Müller, 2019b), mice (Wang et al., 2010), rats (Plomp et al., 1992), and humans (Cull-Candy et al., 1980). Furthermore, there is recent evidence for PHP in the mouse cerebellum (Delvendahl et al., 2019a). The molecular mechanisms underlying PHP are best understood at the Drosophila NMJ (Delvendahl and Müller, 2019b), because this system is amenable to electrophysiology-based genetic screens (Dickman and Davis, 2009; Müller et al., 2011; Delvendahl and Müller, 2019b). At this synapse, pharmacological or genetic impairment of glutamate receptor (GluR) activity triggers a retrograde signal that enhances presynaptic release, thereby precisely compensating for this perturbation (Petersen et al., 1997; Frank et al., 2006). PHP can be induced within minutes after pharmacological receptor impairment (Frank et al., 2006). Severing the motoneuron axons forming the Drosophila NMJ in close vicinity of the NMJ does not impair PHP upon pharmacological receptor impairment (Frank et al., 2006), indicating that the mechanisms underlying rapid PHP expression act locally at the synapse. Moreover, pharmacological inhibition of protein synthesis by cycloheximide does not affect PHP after pharmacological receptor impairment at the Drosophila NMJ (Frank et al., 2006), suggesting that de novo protein synthesis is not required for PHP expression on rapid time scales. By contrast, acute or sustained disruption of the presynaptic proteasome blocks PHP (Wentzel et al., 2018), demonstrating that presynaptic UPS-mediated proteostasis is required for PHP. Furthermore, genetic data link UPS-mediated degradation of two proteins, Dysbindin and RIM, to PHP (Wentzel et al., 2018). Yet, it is currently unclear how the UPS controls PHP. Based on the critical role of E3 ligases in UPS function, we hypothesized an involvement of E3 ligases in PHP.

Here, we realized an electrophysiology-based genetic screen to systematically analyze the role of E3 ligases in neurotransmitter release regulation and PHP at the Drosophila NMJ. This screen discovered that the E3 ligase-encoding gene thin, an ortholog of human TRIM32 (LaBeau-DiMenna et al., 2012; Domsch et al., 2013), controls neurotransmitter release and PHP. We provide evidence that thin regulates the number of release-ready synaptic vesicles through dysbindin, a gene linked to PHP in Drosophila and schizophrenia in humans.

Results

An electrophysiology-based genetic screen identifies thin

To systematically test the roles of E3 ligases in PHP, we first generated a list of genes predicted to encode E3 ligases in D. melanogaster. To this end, we browsed the D. melanogaster genome for known E3-ligase domains (Du et al., 2011; Ketosugbo et al., 2017). Moreover, we included homologs of predicted vertebrate E3 ligases (see Figure 1—figure supplement 1). This approach yielded 281 putative E3 ligase-encoding genes (Figure 1A), significantly higher than previously predicted for D. melanogaster (207 genes; Du et al., 2011). To explore the relationship between the number of E3 ligase-encoding genes and the number of protein-coding genes, we plotted the number of putative E3 ligase-encoding genes over the total protein-coding gene number of three species and compared it to the relationship between protein kinase-encoding genes and genome size (Figure 1A). The relatively constant ratio between the predicted number of E3 ligase-encoding genes and genome size across species (~0.02–0.03; Figure 1A; Ketosugbo et al., 2017), suggests an evolutionarily conserved stoichiometry between E3 ligases and target proteins, similar to protein kinases (Figure 1A). Hence, a core mechanism of the UPS – protein ubiquitination – is likely conserved in D. melanogaster.

Figure 1 with 2 supplements see all
An electrophysiology-based genetic screen identifies thin as a synaptic homeostasis gene.

(A) The number of putative E3 ubiquitin ligase-encoding genes (E3) and protein kinase-encoding genes (PK) as a function of total protein-coding gene number of C. cerevisiae, D. melanogaster, and H. sapiens. Note the similar relationship between E3 number or PK number and total protein-coding gene number across species. (B) Top: 157 E3 ligase-encoding genes and 11 associated genes (180 lines; presynaptic RNAi expression, elavc155-Gal4>UAS RNAi, or mutants, note that some genes were targeted by more than one line) were tested using two-electrode voltage clamp analysis at the Drosophila neuromuscular junction (NMJ) in the presence of the glutamate receptor (GluR) antagonist philanthotoxin-443 (‘PhTX’) to assess presynaptic homeostatic plasticity (PHP) (see Materials and methods). Bottom: Exemplary miniature excitatory postsynaptic potentials (mEPSPs) and action potential (AP)-evoked excitatory postsynaptic currents (EPSCs) recorded from wild-type (WT), WT in the presence of PhTX (‘WT + PhTX’), and a PHP mutant in the presence of PhTX (‘PHP mutant + PhTX’). Note the decrease in mEPSP amplitude after PhTX treatment, indicating GluR inhibition, and the similar EPSC amplitude between WT and WT + PhTX, suggesting PHP. Small EPSC amplitudes in the presence of PhTX (red arrow) imply a defect in PHP or baseline synaptic transmission. (C) Histogram of mean mEPSP amplitudes for each transgenic or mutant line (mean n = 4 NMJs per line, range 3–12; N = 180 lines) following PhTX treatment. WT averages under control conditions (‘WT’, n = 16) and in the presence of PhTX (‘WT + PhTX’, n = 16) are shown as gray and black arrows, respectively. (D) Histogram of mean EPSC amplitudes (as in C). The red bars indicate transgenic or mutant lines with EPSC amplitudes significantly different from WT in the presence of PhTX (black arrow). (E) Volcano plot of the ratio between the mean EPSC amplitude of a transgenic or mutant line and WT (‘EPSCx/EPSCWT’) in the presence of PhTX (p values from one-way analysis of variance [ANOVA] with Tukey’s multiple comparisons). Transgenic or mutant lines with mean EPSC amplitude changes with p ≤ 0.01 (dashed line) are shown in red. A deletion in the gene thin (CG15105; thinΔA; LaBeau-DiMenna et al., 2012) that was selected for further analysis is shown as a filled red circle. One-way ANOVA with Tukey’s multiple comparisons was performed for statistical testing (C–E).

After prioritizing for evolutionarily conserved genes that were shown or predicted to be expressed in the nervous system (Figure 1—figure supplement 1), we investigated PHP after genetic perturbation of 157 putative E3 ligase genes and 11 associated genes (180 lines, Supplementary file 1, Figure 1B). Specifically, we recorded spontaneous miniature excitatory postsynaptic potentials (mEPSPs) and action potential (AP)-evoked excitatory postsynaptic currents (EPSCs) after applying subsaturating concentrations of the GluR antagonist philanthotoxin-443 (PhTX) for 10 min (20 μM; extracellular Ca2+ concentration, 1.5 mM). At wild-type (WT) NMJs, PhTX treatment significantly reduced mEPSP amplitude compared to untreated controls (Figure 1C, black and gray arrows), indicating GluR perturbation. By contrast, AP-evoked EPSC amplitudes were similar between PhTX-treated and untreated WT NMJs (Figure 1D, black and gray arrows). Together with a reduction in mEPSP amplitude, a similar EPSC amplitude suggests a homeostatic increase in neurotransmitter release after PhTX treatment in WT, consistent with PHP (Frank et al., 2006). PhTX also reduced mean mEPSP amplitudes in the 180 transgenic or mutant lines (either presynaptic/neuronal RNAi expression, elavc155-Gal4>UAS RNAi; or mutations within the respective coding sequence, see Materials and methods) compared to untreated WT controls (Figure 1C). Moreover, the mean EPSC amplitude of the majority of the tested lines did not differ significantly from the mean WT EPSC amplitudes recorded at PhTX-treated NMJs (Figure 1D, compare white bars with black arrow). The combination of a decrease in mEPSP amplitude and largely unchanged EPSC amplitude indicates that the majority of the tested lines likely display PHP. We also identified 21 transgenic or mutant lines with significantly smaller EPSC amplitudes compared to PhTX-treated WT NMJs, and two lines with increased EPSC amplitudes (Figure 1D, E, red data). The lines with smaller EPSC amplitudes represent candidate transgenic or mutant lines with disrupted PHP. One of the mutant lines with significantly smaller EPSC amplitudes in the presence of PhTX was a previously described deletion of the gene thin/abba (tn, CG15105), henceforth called thin (thinΔA; LaBeau-DiMenna et al., 2012; Figure 1E, filled red data). thin encodes an E3 ligase with a N-terminal tripartite motif (TRIM), which contains one RING-finger domain, two zinc-finger domains (B1 box and B2 box), and its associated coiled-coil region, followed by a disordered region and C-terminal NHL repeats (Figure 1—figure supplement 2). Based on this domain composition, thin likely represents the Drosophila ortholog of human TRIM32 (Figure 1—figure supplement 2), consistent with earlier work (LaBeau-DiMenna et al., 2012). thin was selected for further analysis.

Presynaptic thin promotes PHP

In the genetic screen, we compared synaptic transmission between a given genotype and WT controls in the presence of PhTX (Figure 1C–E). Hence, the small EPSC amplitude of thinΔA mutants seen after PhTX application could be either due to impaired PHP, or a defect in baseline synaptic transmission. To distinguish between these possibilities, we next quantified synaptic transmission in the absence and presence of PhTX in thinΔA mutants (Figure 2). Similar to WT controls, PhTX application significantly reduced mEPSC amplitude by ~40% in thinΔA mutants (Figure 2A, B), suggesting similar receptor impairment. At WT synapses, EPSC amplitudes were similar in the absence and presence of PhTX (Figure 2A, C). In combination with the decrease in mEPSC amplitude (Figure 2B), PhTX incubation increased quantal content (EPSC amplitude/mEPSC amplitude) in WT (Figure 2D), indicating homeostatic release potentiation. By contrast, PhTX treatment significantly reduced EPSC amplitudes in thinΔA mutants (Figure 2A, C) and did not increase quantal content (Figure 2D). These data show that thin is required for acute PHP expression.

Figure 2 with 1 supplement see all
Homeostatic plasticity requires presynaptic thin.

(A) Representative excitatory postsynaptic currents (EPSCs) (individual sweeps and averages are shown in light colors and black, respectively), and mEPSCs (insets) of wild-type (WT) (gray), thinΔA mutants (red), presynaptic thin expression in thinΔA mutants (elavc155-Gal4>UAS-thin; thinΔA, ‘thinΔA pre. rescue’, blue), and postsynaptic thin expression in thinΔA mutants (24B-Gal4>UASthin; thinΔA, ‘thinΔA post. rescue’, green) in the absence and presence of philanthotoxin-443 (PhTX) (‘+PhTX’, darker colors). Stimulation artifacts were blanked for clarity. Note the decreased EPSC amplitudes at PhTX-treated thinΔA mutant neuromuscular junctions (NMJs) and thinΔA post. rescue NMJs, indicating impaired presynaptic homeostatic plasticity (PHP). Mean mEPSC amplitudes (B), EPSC amplitudes (C), quantal content after PhTX treatment normalized to the respective untreated control (D), in the absence (‘−’) and presence (‘+’) of PhTX, as well as baseline quantal content of the indicated genotypes in the absence (‘−’) of PhTX normalized to WT (E). Note that PhTX did not enhance quantal content in thinΔA mutants (D), indicating impaired PHP. Also note the increased quantal content under baseline conditions in thinΔA mutants (E), suggesting increased release. The PHP and baseline synaptic transmission defects are restored upon presynaptic thin expression in the mutant background. Mean ± standard error of the mean (SEM) (WT − PhTX: n = 14, WT + PhTX: n = 13; thinΔA − PhTX: n = 18; thinΔA + PhTX: n = 21; pre. res. − PhTX: n = 11; pre. res.+ PhTX: n = 10; post. res. − PhTX: n = 25; post. res.+ PhTX: n = 24); *p < 0.05; **p < 0.01; ***p < 0.001; n.s.: not significant; two-way analysis of variance (ANOVA) followed by Tukey’s post hoc test (B–D) and one-way ANOVA with Tukey’s multiple comparisons (E).

To test if presynaptic or postsynaptic thin promotes PHP, and if the PHP defect is indeed caused by loss of thin, we assessed PHP after presynaptic or postsynaptic expression of a thin transgene in the thinΔA mutant background. PhTX treatment significantly reduced mEPSC amplitudes after neural/presynaptic (elavc155-Gal4) or postsynaptic (24B-Gal4) expression of thin (UAS-thin) in thinΔA mutants (Figure 2A, B). After presynaptic thin expression in thinΔA mutants (presynaptic rescue or ‘pre. rescue’), quantal content was significantly increased upon PhTX treatment (Figure 2D, blue data), and EPSC amplitudes were restored toward control levels in the absence of PhTX (Figure 2A, C, blue data). Note that the partial rescue may be due to thin overexpression or defects in muscle architecture (LaBeau-DiMenna et al., 2012). By contrast, quantal content was similar between PhTX-treated and untreated NMJs after postynaptic thin expression in the thinΔA mutant background (postsynaptic rescue or ‘post. rescue’; Figure 2D, green data), and PhTX application reduced EPSC amplitudes (Figure 2A, C, green data). Thus, presynaptic, but not postsynaptic thin expression enhanced quantal content after PhTX treatment in the thinΔA mutant background (Figure 2D), implying a presynaptic role for thin in PHP.

We also noted a decrease in mEPSC amplitude in thinΔA mutants compared to WT in the absence of PhTX (Figure 2A, B), which is most likely due to impaired muscle architecture in thinΔA mutants (LaBeau-DiMenna et al., 2012; Domsch et al., 2013). Postsynaptic, but not presynaptic thin expression, significantly increased mEPSC amplitudes toward WT levels in the thinΔA mutant background (Figure 2A, B), suggesting that postsynaptic thin is required for normal mEPSC amplitude levels. Furthermore, thinΔA mutants displayed a significant increase in quantal content compared to WT under baseline conditions in the absence of PhTX (Figure 2E), which was rescued by presynaptic, but not postsynaptic thin expression (Figure 2E). These data are consistent with the idea that presynaptic thin represses release under baseline conditions (see Figure 4, Figure 6). By extension, the increased release under baseline conditions in thinΔA mutants may partially occlude PHP in response to receptor perturbation (see Discussion).

At the Drosophila NMJ, genetic ablation of the GluRIIA subunit in GluRIIASP16 mutants reduces quantal size and induces sustained PHP (Petersen et al., 1997). To test if thin is required for sustained PHP expression, we generated recombinant flies carrying the GluRIIASP16 and the thinΔA mutation (‘GluRIIASP16, thinΔA’). While we observed a significant increase in quantal content in GluRIIASP16 mutants compared to wild type (Figure 2—figure supplement 1), indicating sustained PHP expression, there was no increase in quantal content in GluRIIASP16, thinΔA double mutants compared to thinΔA mutants (Figure 2—figure supplement 1). Hence, thin is also necessary for sustained PHP expression, providing independent evidence for its role in homeostatic release regulation.

Changes in NMJ development unlikely underlie the PHP defect in thin mutants

The PHP defect and the release enhancement under baseline conditions after presynaptic thin perturbation may arise from impaired synaptic development. To test this possibility, we investigated NMJ morphology in thin mutants (Figure 3). Immunostainings with an antibody detecting neuronal membrane (anti-horseradish peroxidase, ‘HRP’; Figure 3A; Jan and Jan, 1982) revealed no changes in HRP area in thinΔA mutants or after presynaptic rescue (thinΔA; elavc155-Gal4>UAS thin), and a trend toward increased HRP area after postsynaptic rescue (thinΔA; 24BGal4>UAS thin) compared to WT (Figure 3B). Analysis of the active-zone marker Bruchpilot (anti-Bruchpilot, ‘Brp’; Kittel et al., 2006) uncovered no changes in Brp puncta number per NMJ in thinΔA mutants or after presynaptic rescue, and a slight increase after postsynaptic rescue compared to WT (Figure 3A, C). Brp density (Brp puncta #/HRP area) was unchanged in thinΔA mutants or after postsynaptic rescue, and slightly increased after presynaptic rescue (Figure 3D). Finally, we observed a decrease in Brp puncta intensity in thinΔA mutants and upon presynaptic rescue (Figure 3E). In principle, these morphological alterations could be related to the PHP defect, or the release enhancement seen in thinΔA mutants. However, while HRP area and Brp puncta number were unchanged in thinΔA mutants (Figure 3B, C), PHP was blocked, and baseline synaptic transmission enhanced (Figure 2). In addition, postsynaptic thin expression in WT induced an increase in HRP area and Brp puncta number (Figure 3—figure supplement 1B, C), but neither impaired PHP nor enhanced release (Figure 3—figure supplement 1F–K). Furthermore, Brp intensity was decreased after presynaptic rescue (Figure 3E) and postsynaptic thin overexpression in WT (Figure 3—figure supplement 1E), whereas synaptic physiology was unchanged in these genotypes (Figure 2, Figure 3—figure supplement 1F–K). Conversely, Brp intensity was unchanged after presynaptic thinRNAi expression (elavc155-Gal4>UAS-thinRNAi), while PHP was blocked and baseline synaptic transmission enhanced (Figure 4, Figure 4—figure supplement 1). Collectively, these data suggest that the morphological changes seen after thin perturbation are separable from synaptic physiology. Thus, although we cannot rule out that changes in NMJ morphology contribute to the PHP defect or the increase in release in thin mutants, we consider this possibility unlikely (see Discussion).

Figure 3 with 1 supplement see all
Slight alterations in neuromuscular junction (NMJ) morphology upon genetic thin manipulations.

(A) Maximum intensity projection of a wild-type (WT) (left) and thinΔA mutant NMJ (right) (muscle 6) stained against the Drosophila neuronal membrane marker anti-HRP (‘HRP’) and the active-zone marker Bruchpilot (‘Brp’); scale bar, 10 µm. Mean HRP area per NMJ ‘HRP area’ (B), Brp puncta number per NMJ ‘Brp puncta #’ (C), Brp puncta number/HRP area per NMJ ‘Brp density’ (D), and Brp puncta fluorescence intensity (E) of the indicated genotypes (‘Postsynaptic rescue’: 24B-Gal4>UAS-thin; thinΔA; ‘presynaptic rescue’: elavc155-Gal4>UASthin; thinΔA). Although changes in the recorded parameters may contribute to changes in synaptic physiology, altered NMJ morphology was separable from synaptic physiology (see Results, Discussion, Figure 2, Figure 3—figure supplement 1, Figure 4, Figure 4—figure supplement 1). Mean ± standard error of the mean (SEM); WT: n = 10, thinΔA: n = 8, pre. res.: n = 12; post. res.: n = 13; *p < 0.05; **p < 0.01; ***p < 0.001; n.s.: not significant; Student’s t-test.

Figure 4 with 1 supplement see all
Thin negatively regulates release-ready vesicle number.

(A) Representative excitatory postsynaptic currents (EPSCs) (individual sweeps and averages are shown in light colors and black, respectively), and mEPSCs (insets) of controls (elavc155-Gal4>UAS-mCherryRNAi, ‘Ctrl.’, gray) and presynaptic thinRNAi (elavc155-Gal4>UAS-thinRNAi, ‘thinRNAi (pre)’, red). Mean mEPSC amplitudes (B), EPSC amplitudes (C), and quantal content (D) of the indicated genotypes. (E) Representative EPSC train (60 Hz, 60 stimuli, top) and cumulative EPSC amplitudes (‘cum. EPSC’, bottom) of control and presynaptic thinRNAi. The blue line is a line fit to the last 15 cum. EPSC amplitudes that was back-extrapolated to t = 0 (see Materials and methods). Mean readilyreleasable vesicle pool (RRP) size (cum. EPSC/mEPSC) (F), release probability (‘pr’, EPSC1/cum. EPSC) (G), and paired-pulse ratio (‘PPR’, EPSC2/EPSC1) (H) of the indicated genotypes. Note the increase in EPSC amplitude and RRP size in presynaptic thinRNAi. Mean ± standard error of the mean (SEM); Ctrl.: n = 16, thinRNAi: n = 17; *p < 0.05; ***p < 0.001; n.s.: not significant; Student’s t-test.

thin negatively regulates release-ready vesicle number

Having established that thin is required for acute and sustained PHP expression, we next explored the role of thin in the regulation of neurotransmitter release under baseline conditions. thinΔA mutants display increased neurotransmitter release in the absence of PhTX, and this increase in release is rescued by presynaptic thin expression (Figure 2). We also noted a decrease in mEPSC amplitude in thinΔA mutants (Figure 2B), which may confound conclusions regarding presynaptic thin function. We therefore focused our further analyses on the effects of presynaptic thinRNAi expression.

First, we tested PHP after presynaptic thinRNAi expression (elavc155-Gal4>UAS-thinRNAi) and observed a complete PHP block (Figure 4—figure supplement 1F–I), providing independent evidence for a role of presynaptic thin in PHP. To elucidate the mechanisms through which thin negatively modulates release under baseline conditions, we probed the size of the readily releasable pool of synaptic vesicles (RRP) and neurotransmitter release probability (pr) after presynaptic thin perturbation (Figure 4). Presynaptic thinRNAi expression (elavc155-Gal4>UAS-thinRNAi) significantly increased EPSC amplitudes and quantal content (Figure 4A, C, D), with no significant effects on mEPSC amplitudes compared to controls (elavc155-Gal4>UAS-mCherryRNAi; Figure 4A, B), suggesting that presynaptic thin represses release, consistent with the data obtained from thinΔA mutants (Figure 2). Note that the smaller mEPSC and EPSC amplitudes under baseline conditions after postsynaptic thin rescue (Figure 2B, C) compared to thinRNAi (Figure 4B, C) are most likely due to non-endogenous postsynaptic Thin levels caused by thin overexpression in the thinΔA mutant background. Next, we estimated RRP size using cumulative EPSC amplitude analysis during high-frequency stimulation (60 Hz; Weyhersmüller et al., 2011; Müller et al., 2012; Figure 4E). This analysis revealed a significantly larger RRP size upon presynaptic thinRNAi expression compared to controls (Figure 4E, F), implying that presynaptic thin negatively regulates RRP size. We then estimated pr based on the ratio between the first EPSC amplitude of the stimulus train and the cumulative EPSC amplitude, and observed no significant pr differences between presynaptic thinRNAi and controls (Figure 4G). We noted that the paired-pulse ratio between the second and first EPSC amplitude during 60 Hz stimulation was slightly increased after presynaptic thinRNAi expression compared to controls (Figure 4H), implying a slight decrease in pr. These data suggest that the increase in release after presynaptic thinRNAi expression is unlikely caused by an increase in pr, and that presynaptic thinRNAi expression may even slightly decrease pr. Presynaptic thinRNAi expression also slightly increased Brp number (Figure 4—figure supplement 1), which may contribute to the increase in release after presynaptic thinRNAi expression (see Discussion). However, our analysis of thinΔA mutants implies that changes in NMJ size unlikely underlie the defects in synaptic physiology after presynaptic loss of thin (Figures 2 and 3). Together, we conclude that presynaptic thin opposes release by limiting the number of release-ready synaptic vesicles with largely unchanged pr.

Thin localizes in proximity to Dysbindin

TRIM32, Thin’s predicted human ortholog (Figure 1—figure supplement 2), ubiquitinates Dysbindin and targets it for degradation in cultured human cells (Locke et al., 2009). dysbindin, in turn, is required for PHP at the Drosophila NMJ (Dickman and Davis, 2009), and genetic evidence suggests that the UPS controls Dysbindin under baseline conditions and during PHP at the Drosophila NMJ (Wentzel et al., 2018). We therefore explored the relationship between Thin and Dysbindin. First, we investigated the localization of Thin in relation to Dysbindin within synaptic boutons (Figure 5). Previous studies suggest very low endogenous Dysbindin levels that preclude direct immunohistochemical analysis at the Drosophila NMJ (Dickman and Davis, 2009; Wentzel et al., 2018). However, presynaptic expression of a fluorescently tagged dysbindin transgene revealed that Dysbindin localizes in close proximity to synaptic vesicle markers (Dickman and Davis, 2009; Figure 5—figure supplement 1A–C). The localization of fluorescently tagged Dysbindin likely overlaps with the one of endogenous Dysbindin, as its presynaptic expression rescues the PHP defect in dysbindin mutants (Dickman and Davis, 2009). Although we observed anti-Thin fluorescence in close proximity to Brp (Figure 5—figure supplement 1D, E), thin expression in Drosophila muscles makes it difficult to distinguish between presynaptic and postsynaptic Thin (LaBeau-DiMenna et al., 2012; Figure 5—figure supplement 1D, E). This prompted us to analyze the localization of fluorescently tagged Thin, which we expressed presynaptically (elavc155-Gal4>UAS-thinmCherry), in relation to Dysbindin. Presynaptic ThinmCherry partially overlapped with presynaptic fluorescently tagged Dysbindin (elavc155-Gal4>UAS-dysbvenus) at confocal resolution (Figure 5A and B). The localization of fluorescently tagged Thin also likely overlaps with endogenous Thin, because presynaptic thin expression restores PHP and synaptic transmission in thin mutants (Figure 2). As indicated by the line profile across a bouton (Figure 5B), Dysbindin and Thin fluorescence intensity increased toward the bouton periphery (Figure 5B), similar to synaptic vesicle markers, such as synapsin (Figure 5—figure supplement 1A, B). With stimulated emission depletion microscopy with time-gated detection (gSTED), fluorescently tagged Thin and Dysbindin appeared as distinct spots (Figure 5C). To investigate the relationship between fluorescently tagged Thin and Dysbindin, we quantified the nearest-neighbor distance (NND) between Thin and Dysbindin spots (Figure 5D; see Materials and methods). This analysis revealed significantly smaller NNDs between ThinmCherry and Dysbvenus spots than expected from random spot distributions (Figure 5E), implying a relationship between Thin and Dysbindin localization within synaptic boutons. Based on the proximity between Dysbindin and synaptic vesicle markers (Dickman and Davis, 2009; Figure 5—figure supplement 1A–C), these data indicate that a fraction of Thin localizes in the vicinity of Dysbindin and synaptic vesicles.

Figure 5 with 2 supplements see all
Thin localizes in close proximity to Dysbindin.

(A) Confocal maximum intensity projection of a representative neuromuscular junction (NMJ) branch (muscle 6–7) after presynaptic coexpression (elavc155-Gal4) of venus-tagged Dysbindin (UAS-venus-Dysbindin, ‘Dysbvenus’, green) and mCherry-tagged Thin (UAS-mCherry-thin, ‘ThinmCherry’, magenta) detected with anti-GFP and anti-DsRed, respectively. (B) Single plane of the synaptic bouton highlighted by the white square in (A) with corresponding line profile (right). The yellow line demarks the location of the line profile. (C) gSTED image of the synaptic bouton shown in (B) with corresponding line profile (right). Scale bar, A: 5 µm; B, C: 2 µm. Note the partial overlap between ThinmCherry and Dysbindinvenus at confocal and STED resolution. (D) Left: Schematic of nearest-neighbor (NND) analysis between ThinmCherry and Dysbindinvenus puncta at STED resolution. Right: ThinmCherry puncta (‘+’, maximum locations, see Materials and methods) and the NNDs and locations of Dysbindinvenus puncta (color code denotes NND) of a representative bouton. (E) Histogram of mean ThinmCherry − Dysbindinvenus NND per bouton of the recorded gSTED data (blue), or after randomized punctum distribution (gray, see Materials and methods). N = 10 NMJs, average n = 13 boutons per NMJ for data and simulations. Observed vs. randomized NNDs, p < 0.001; Student’s t-test.

To provide independent evidence for a relationship between Thin and Dysbindin localization, and to explore if Thin acts as an E3 ubiquitin ligase for Dysbindin in Drosophila, we turned to cultured Drosophila Schneider 2 (S2) cells. Interestingly, while anti-Thin fluorescence was homogenously distributed within S2 cells under control conditions (Figure 5—figure supplement 2A), dysbindin (dysbvenus) overexpression led to a redistribution of anti-Thin fluorescence into clusters that localized in close proximity to anti-Dysbindin clusters (Figure 5—figure supplement 2A). Moreover, anti-Thin and anti-Dysbindin fluorescence intensities were highly correlated (Figure 5—figure supplement 2B), suggesting a possible interaction between Thin and Dysbindin in S2 cells, similar to the Drosophila NMJ (Figure 5). Next, we assessed whether Thin expression affects Dysbindin abundance in S2 cells by western blot analysis. We observed a decrease in Dysbvenus levels upon increasing ThinHA expression levels (Figure 5—figure supplement 2C, D). Although we cannot exclude the possibility that Thin overexpression induced artificial Dysbindin ubiquitination by excess enzyme binding with low affinity, these data are consistent with the idea that Thin acts as an E3 ligase for Dysbindin in Drosophila, similar to TRIM32 in humans (Locke et al., 2009).

thin represses release through dysbindin

We next explored a possible genetic interaction between thin and dysbindin in the context of synaptic physiology. As thin and dysbindin mutants alone disrupt PHP, the analysis of double mutants would not be informative. We therefore investigated baseline synaptic transmission after presynaptic thinRNAi expression in the dysbindin mutant background (Figure 6). Neither presynaptic thinRNAi expression (elavc155-Gal4>UAS-thinRNAi) in the WT background, nor in the dysb1 mutant background affected mEPSC amplitude (Figure 6A, B). While presynaptic thinRNAi expression enhanced EPSC amplitude and quantal content in the WT background (Figure 6C, D; see also Figure 4), presynaptic thinRNAi expression neither affected EPSC amplitude (Figure 6C) nor quantal content (Figure 6D) in the dysb1 mutant background. These data provide genetic evidence that thin negatively controls release through dysbindin (Figure 6E).

Thin represses release through dysbindin.

(A) Representative excitatory postsynaptic currents (EPSCs) (individual sweeps and averages are shown in light colors and black, respectively), and mEPSCs (insets) of wild-type (WT) (gray) and presynaptic thinRNAi (elavc155-Gal4>UAS-thinRNAi, ‘+thinRNAi (pre)’, dark gray), dysb1 mutants (light red), and presynaptic thinRNAi in the dysb1 mutant background (elavc155-Gal4/Y; UAS-thinRNAi/+; dysb1, ‘+thinRNAi (pre)’, dark red). Mean mEPSC amplitudes (B), EPSC amplitudes (C), and quantal content (D) of the indicated genotypes. Note that presynaptic thinRNAi expression increases EPSC amplitude and quantal content in WT, but not in dysb1 mutants. Mean ± standard error of the mean (SEM); WT: n = 17, elavc155-Gal4>UAS-thinRNAi: n = 17, dysb1: n = 12, elavc155-Gal4/Y; UAS-thinRNAi/+; dysb1: n = 12; *p < 0.05; **p < 0.01; ***p < 0.001; n.s.: not significant; two-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. (E) Working model: Our genetic data support a model in which thin controls neurotransmitter release (‘Release’) through negative regulation of dysbindin (‘dysb’).

Discussion

Employing an electrophysiology-based genetic screen targeting 157 E3 ligase-encoding genes at the Drosophila NMJ, we discovered that a mutation in the E3 ligase-encoding gene thin disrupts acute and sustained PHP. Presynaptic loss of thin led to increased release and RRP size, largely independent of gross synaptic morphological changes. Thin and Dysbindin localize in proximity within synaptic boutons, and biochemical evidence suggests that Thin degrades Dysbindin in vitro. Finally, presynaptic thin perturbation did not enhance release in the dysbindin mutant background, providing genetic evidence that thin represses release through dysbindin. As thin and dysbindin are required for PHP, these data are consistent with a model in which thin controls neurotransmitter release during PHP and under baseline conditions through dysbindin.

Our study represents the first systematic investigation of E3 ligase function in the context of synaptic transmission. A considerable fraction of the transgenic lines tested (11%) displayed a decrease in EPSC amplitude after PhTX treatment (Figure 1C–E). These E3 ligase-encoding genes may either be required for PHP and/or baseline synaptic transmission. Previous PHP screens in the same system identified PHP mutants with a hit rate of ~3% (Dickman and Davis, 2009; Müller et al., 2011). Thus, our data indicate that E3 ligase function plays a special role in PHP and/or baseline synaptic transmission. As more transgenic or mutant lines exhibited a decrease in synaptic transmission, we conclude that the net effect of E3 ligases is to promote synaptic transmission at the Drosophila NMJ. Given the evolutionary conservation of most E3 ligase-encoding genes tested in this study (Figure 1, Supplementary file 1), the results of our screen may allow predicting the roles of the tested E3 ligases in neurotransmitter release regulation in other systems.

Previous studies linked E3 ligases to synaptic development and synaptic function at the Drosophila NMJ (Wan et al., 2000; van Roessel et al., 2004). For instance, the E3 ligase highwire (hiw) restrains synaptic growth and promotes evoked synaptic transmission at the Drosophila NMJ (Wan et al., 2000). Similarly, the deubiquitinating protease fat facets represses synaptic growth and enhances synaptic transmission (DiAntonio et al., 2001). Although different molecular pathways have been implicated in hiw-dependent regulation of synaptic growth and function (Russo et al., 2019), it is generally difficult to disentangle effects on synaptic morphology from synaptic function. thin and its mammalian ortholog TRIM32 are required for maintaining the cytoarchitecture of muscle cells (Kudryashova et al., 2005; LaBeau-DiMenna et al., 2012; Cijsouw et al., 2018). Hence, the changes in synaptic transmission described in the present study may be a secondary consequence of impaired muscle structure. However, presynaptic thin expression in the thin mutant background restored presynaptic function under baseline conditions and during homeostatic plasticity (Figure 2). Conversely, while postsynaptic thin expression largely rescued the defects in muscle morphology in thin mutants, the defects in synaptic function persisted. These genetic data suggest that the neurotransmitter release impairment under baseline condition and during PHP in thin mutants is unlikely caused by muscular dystrophy.

We also noted a slight increase in NMJ size and/or Brp number after postsynaptic rescue in the thin mutant background (Figure 3) or following presynaptic thinRNAi expression (Figure 4—figure supplement 1). Moreover, Brp intensity was decreased in thinΔA mutants, after presynaptic rescue (Figure 3), or after postsynaptic thin overexpression in WT (Figure 3—figure supplement 1). The reasons for the increase in NMJ size or the decrease in Brp intensity after thin manipulations are unknown, but point at a potential dysregulation of thin-dependent pathways regulating NMJ size and Brp abundance. In principle, the changes in synaptic physiology observed in these genotypes may be a consequence of altered NMJ morphology. However, the observed changes in NMJ morphology were separable from changes in synaptic physiology (Figures 2 and 3, Figure 3—figure supplement 1), implying that presynaptic thin regulates neurotransmitter release under baseline conditions and during homeostatic plasticity largely independent of changes in synaptic morphology.

We revealed that presynaptic thin perturbation results in enhanced neurotransmitter release (Figures 2, 4 and 6), indicating that the E3 ligase Thin represses neurotransmitter release under baseline conditions. Notably, there are just a few molecules that have been implicated in repressing neurotransmitter release, such as the SNARE-interacting protein tomosyn (Hatsuzawa et al., 2003; Chen et al., 2011), or the RhoGAP crossveinless-c (Pilgram et al., 2011). How could the E3 ligase Thin oppose neurotransmitter release? We discovered that dysbindin is required for the increase in release induced by presynaptic thin perturbation (Figure 6). Moreover, Thin localizes in close proximity to Dysbindin in synaptic boutons (Figure 5), and we provide evidence that Thin likely degrades Dysbindin in vitro (Figure 5—figure supplement 2), similar to its mammalian ortholog TRIM32 (Locke et al., 2009). At the Drosophila NMJ, 26S-proteasomes are transported to presynaptic boutons (Kreko-Pierce and Eaton, 2017), where they degrade proteins on the minute time scale (Speese et al., 2003; Wentzel et al., 2018). Previous genetic data suggest a positive correlation between Dysbindin levels and neurotransmitter release (Dickman and Davis, 2009; Wentzel et al., 2018), and there is genetic evidence for rapid, UPS-dependent degradation of Dysbindin at the Drosophila NMJ (Wentzel et al., 2018). In combination with these previous observations, our data are consistent with the idea that Thin opposes release by acting on Dysbindin. Although the low abundance of endogenous Dysbindin at the Drosophila NMJ precludes direct analysis of Dysbindin levels (Dickman and Davis, 2009), we speculate that Thin decreases Dysbindin abundance by targeting it for degradation. Alternatively, Thin may modulate Dysbindin function through mono-ubiquitination. Genetic data suggest that Dysbindin interacts with the SNARE protein SNAP25 through Snapin (Dickman et al., 2012). Hence, Thin-dependent regulation of Dysbindin may modulate release via Dysbindin’s interaction with the SNARE complex.

Our study identified a crucial role for thin in PHP. How does the increase in neurotransmitter release in thin mutants under baseline conditions relate to the PHP defect? mEPSC amplitudes were decreased in thin mutants, after presynaptic and postsynaptic rescue (Figure 2), and largely unchanged after presynaptic thinRNAi expression (Figure 4). The decrease in mEPSC amplitude implies a postsynaptic role of thin in regulating quantal size, possibly by regulating GluR levels (Figure 2—figure supplement 1). Quantal content was increased in thin mutants, after postsynaptic rescue (Figure 2), and after presynaptic thinRNAi expression (Figure 4). Together, these data imply that the increase in quantal content under baseline conditions induced by presynaptic thin manipulations is separable from a decrease in miniature amplitude. By definition, PHP is induced by a relative decrease in miniature amplitude. Given that quantal content increased after presynaptic thin manipulations independent of changes in miniature amplitude, we consider it unlikely that the increased quantal content under baseline conditions represents a homeostatic response. Could the increase in release after presynaptic thin perturbation simply occlude PHP? The relative increase in release during PHP of WT synapses exceeds the increase in release under baseline conditions in thin mutants. Thus, although we cannot exclude that PHP is solely occluded by enhanced baseline release in thin mutants, we consider this scenario unlikely.

PHP is blocked by acute pharmacological, or prolonged genetic proteasome perturbation at the Drosophila NMJ (Wentzel et al., 2018). Moreover, PHP at this synapse requires dysbindin (Dickman and Davis, 2009), and genetic data suggest UPS-dependent control of a Dysbindin-sensitive vesicle pool during PHP (Wentzel et al., 2018). Based on our finding that thin is required for acute and sustained PHP expression (Figure 2, Figure 2—figure supplement 1), and the links between thin und dysbindin in the context of release modulation outlined above, we propose a model in which Thin-dependent ubiquitination of Dysbindin is decreased during PHP. Given the positive correlation between Dysbindin levels and release (Dickman et al., 2012; Wentzel et al., 2018), the resulting increase in Dysbindin abundance would potentiate release. Further work is needed to test how Thin is regulated during PHP. Thin is the first E3 ubiquitin ligase linked to homeostatic regulation of neurotransmitter release. Interestingly, a recent study revealed a postsynaptic role for Insomniac, a putative adaptor of the Cullin-3 ubiquitin ligase complex, in PHP at the Drosophila NMJ (Kikuma et al., 2019), suggesting a key function of the UPS in both synaptic compartments during PHP at this synapse.

TRIM32, the human ortholog of thin, is required for synaptic down-scaling in cultured hippocampal rat neurons (Srinivasan et al., 2020), as well as long-term potentiation in hippocampal mouse brain slices (Ntim et al., 2020), implying a broader role of this E3 ubiquitin ligase in synaptic plasticity. TRIM32 has been implicated in various neurological disorders, such as depression (Ruan et al., 2014), Alzheimer’s disease (Yokota et al., 2006), autism spectrum disorder (Lionel et al., 2014; Ruan et al., 2014), or attention deficit hyperactivity disorder (Lionel et al., 2011). It will be exciting to explore potential links between TRIM32-dependent control of synaptic homeostasis and these disorders in the future.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (Drosophila melanogaster)thinΔALaBeau-DiMenna et al., 2012
Genetic reagent (Drosophila melanogaster)UAS-abbaLaBeau-DiMenna et al., 2012
Genetic reagent (Drosophila melanogaster)UAS-mCherry-thinThis studyStock is available upon request
Genetic reagent (Drosophila melanogaster)GluRIIASP16Petersen et al., 1997
Genetic reagent (Drosophila melanogaster)dysbindin1Dickman and Davis, 2009
Genetic reagent (Drosophila melanogaster)UAS-thinRNAiPerkins et al., 2015RRID:BDSC_42826
Genetic reagent (Drosophila melanogaster)UAS-mCherryRNAi (P{VALIUM20-mCherry}attP2)Bloomington Drosophila Stock CenterRRID:BDSC_35785
Genetic reagent (Drosophila melanogaster)UAS-venus-dysbindinDickman and Davis, 2009
Genetic reagent (Drosophila melanogaster)elavc155-Gal4Bloomington Drosophila Stock CenterRRID:BDSC_458
Genetic reagent (Drosophila melanogaster)24B-Gal4Bloomington Drosophila Stock CenterRRID:BDSC_1767
Antibodyanti-Bruchpilot (nc82) (mouse monoclonal)DSHB, University of Iowa, USARRID:AB_2314866(1:100)
Antibodyanti-GFP (rabbit polyclonal)Thermo Fisher ScientificThermo Fisher Scientific Cat# G10362, RRID:AB_2536526IF: (1:500)
WB: (1:1000)
Antibodyanti-GFP (mouse mono clonal)Thermo Fisher ScientificThermo Fisher Scientific Cat# A-11120, RRID:AB_221568(1:500)
Antibodyanti-DsRed (mouse monoclonal)Santa Cruz BiotechnologySanta Cruz Biotechnology Cat# sc-390909, RRID:AB_2801575(1:500)
Antibodyanti-SYNORF1 (Synapsin, 3C11) (mouse monoclonal)DSHB, University of Iowa, USARRID:AB_528479(1:250)
Antibodyanti-Thin (guinea pig polyclonal)LaBeau-DiMenna et al., 2012Larva: (1:200)
S2:
(1:400)
Antibodyanti-HRP Alexa-Fluor 647 (goat polyclonal)Jackson ImmunoResearch LabsJackson ImmunoResearch Labs Cat# 123-605-021, RRID:AB_2338967(1:200)
AntibodyAnti-HA (mouse monoclonal)BiolegendBioLegend Cat# 901533, RRID:AB_2801249(1:1000)
AntibodyAnti-BetaTubulin (mouse monoclonal)DSHB, University of Iowa, USADSHB Cat# E7, RRID:AB_528499(1:1000)
AntibodyGoat anti-Mouse IgG (H+L) Secondary Antibody, HRP (goat polyclonal)Thermo Fisher ScientificThermo Fisher Scientific Cat# 31430, RRID:AB_228307(1:2000)
AntibodyGoat anti-Rabbit IgG (H+L) Secondary Antibody, HRP (goat polyclonal)Thermo Fisher ScientificThermo Fisher Scientific Cat# 32460, RRID:AB_1185567(1:2000)
AntibodyAlexa-Fluor anti-mouse 488 (goat polyclonal)Thermo Fisher ScientificThermo Fisher Scientific Cat# A32723, RRID:AB_2633275(1:500)
AntibodyAlexa Fluor anti-guinea pig 555
(goat polyclonal)
Thermo Fisher ScientificThermo Fisher Scientific Cat# A-21435 RRID:AB_2535856(1:400)
AntibodyAtto 594 conjugated anti-mouse (goat polyclonal)Sigma-AldrichSigma-Aldrich Cat# 76,085(1:100)
AntibodyAbberior STAR 635P (goat polyclonal)AbberiorAbberior Cat# ST635P-1002-500 UG, RRID:AB_2893229(1:100)
Chemical compound, drugBouin’s fixativeSigma-AldrichHT-10132
Chemical compound, drugEthanolMerckCAS# 64-17-5
Chemical compound, drugProLong Gold AntifadeThermo Fisher ScientificP36930
Chemical compound, drugPhilanthotoxin-433Santa Cruz BiotechnologyCat# sc-255421
Chemical compound, drugSchneider’s Drosophila mediumGibcoCat# 21720024
Chemical compound, drugFuGENE HDPromegaCat# E2311
Chemical compound, drugParaformaldehydeMerckHT501128
Chemical compound, drugNP-40Thermo Fisher Scientific85,125
Chemical compound, drugDeoxycholateSigma-AldrichD6750
Chemical compound, drugcOmpleteSigma-Aldrich11697498001
Chemical compound, drugECL Prime Western Blotting Detection ReagentGE HealthcareCat# 28980926
Cell line (D. melanogaster)Drosophila Schneider 2 (S2) CellsThermo Fisher ScientificCat# R69007
Commercial assay, kitNitrocellulose membraneAmersham Hibond GE HealthcareCat# 88,018
Recombinant DNA reagentpMT-Gal4AddgeneRRID:Addgene_53366
Software, algorithmFiji / ImageJhttps://fiji.scRRID:SCR_002285Version 1.51n
Software, algorithmClampexAxon CNS, Molecular DevicesRRID:SCR_011323
Software, algorithmLeica Application Suite XLeica MicrosystemsRRID:SCR_013673
Software, algorithmHuygens Softwarehttps://svi.nl/HuygensSoftwareRRID:SCR_014237
Software, algorithmIgor ProWaveMetricsRRID:SCR_000325Version 6.37
Software, algorithmNeuroMaticRothman and Silver, 2018RRID:SCR_004186Version 3.0c
Software, algorithmNumPyhttps://www.numpy.orgRRID:SCR_008633
Software, algorithmSciPyhttps://www.scipy.orgRRID:SCR_008058
Software, algorithmIPythonhttp://ipython.orgRRID:SCR_001658
Software, algorithmNeohttp://neuralensemble.org/neoRRID:SCR_000634
Software, algorithmShapely(Gillies, 2007) https://github.com/shapely/shapely
Software, algorithmRStudio(R Studio Team, 2020)

http://www.rstudio.com/
RRID:SCR_000432Version 2021.09.0
Software, algorithmpwr-package(Champely, 2020)

https://github.com/heliosdrm/pwr
Software, algorithmGNU Image Manipulation Programhttps://www.gimp.org/RRID:SCR_003182Version 2.8.10
Software, algorithmInkscapehttp://www.inkscape.orgRRID:SCR_014479Version 0.92.2
Software, algorithmAffinity Designerhttps://affinity.serif.com/en-us/designer/RRID:SCR_016952Version 1.10.4

Fly stocks and genetics

Request a detailed protocol

Drosophila stocks were maintained at 21–25°C on normal food. The w1118 strain was used as the WT control. GluRIIASP16 mutants (Petersen et al., 1997) and dysbindin1 mutants (Dickman and Davis, 2009) were a kind gift from Graeme Davis’ lab. thinΔA mutants and UAS-abba transgenic flies, now referred to as UAS-thin (LaBeau-DiMenna et al., 2012), were a generous gift from Erika Geisbrecht. The UAS-thinRNAi stock (BDSC stock 42826, Perkins et al., 2015) and the UAS-mCherryRNAi stock (BDSC stock 35785) were obtained from the Bloomington Drosophila Stock Center (BDSC, Bloomington, IN, USA), and the UAS-venus-dysbindin line was provided by Dion Dickman’s lab. For pan-neuronal expression, the elavc155-Gal4 (on the X chromosome) driver line was used and analysis was restricted to male larvae. For expression in muscle cells, we used the 24B-Gal4 driver line. Both driver lines were obtained from the BDSC. Standard second and third chromosome balancer lines (BDSC) and genetic strategies were used for all crosses and for maintaining the mutant lines. For the generation of transgenic flies carrying UAS-mCherry-thin, constructs based on the pUAST-attB vector backbone were injected into the ZP-attP-86Fb fly line harboring a landing site on the third chromosome according to standard procedures (Bischof et al., 2014).

Cell culture and transfection

Request a detailed protocol

Schneider S2 cells were obtained from Thermo Fisher Scientific (‘Gibco Drosophila S2 cells’; Cat# R69007). The supplier’s Master Seed Bank was characterized by isozyme and karyotype analysis, and was tested for contamination of bacteria, yeast, mycoplasma, and virus. We have not independently verified cell line identity or tested for mycoplasma contamination. However, contamination with other cell lines is unlikely, because the used cell line is (1) the only cell line used in the lab, (2) the only Drosophila cell line present at the institute, and (3) cells grow at 25° and in a different medium compared to human cell lines. Cells were used within 10 months after purchase. Schneider S2 cells were cultivated in standard Schneider’s Drosophila medium (Gibco) containing 10% fetal calf serum and 5% penicilin/streptomycin at 25°C. For immunohistochemistry and microscopy, cells were plated on cover slips in 12-well plates with 80% density and transfected with 1.5 μg (total) vector DNA using FuGENE HD Transfection Reagent according to the standard protocol. The following vectors were used: pMT-Gal4 (Addgene), pUAS-mCherry-thin, pUAS-HA-thin, pUAS-venus-dysbindin (Dion Dickman), and empty pUAS to adjust to equal DNA levels. Twenty-four hours after plating, CuSO4 (0.5 mM) was added to the culture for 24 hr to induce the expression of the pMT vector driving Gal4, which in turn drives transcription of UAS constructs.

Plasmid construction

Request a detailed protocol

For the pUAS-mCherry-thin vector, mCherry was cloned into pUAS-attB (Addgene) via EcoRI/NotI using the following primers:

(fw: 5′-GCGAATTCATGGTGAGCAAGGGCGAGGAG-3′, rev: 5′- GCGCGGCCGCCCTTGTACAGCTCGTCCATGCCG-3′).

Thin isoform A (NM_137546.3) was amplified from Drosophila cDNA by PCR using the following primers:

(fw: 5′-CGGCGGCCGCATGGAGCAATTCGAGCAGCTGT-3′, rev: 5′-CGTCTAGAATGAAGACTTGGACGCGGTGATTCTCTCG-3′) and then cloned into the pUAS-mCherry vector via NotI/XbaI.

pUAS-HA-thin was generated by In-Fusion mutagenesis (TaKaRa) from the pUAS-mCherry-thin plasmid with the following primers:

(fw: 5′-AGATTACGCTTATCCATATGATGTTCCAGATTATGCTGGCCGCATGGAGCAATTC-3′ and rev: 5′-GGATAAGCGTAATCTGGAACATCGTATGGGTACATAATTCCCAATTCCCTATTCAGAGT-3′).

Correct cloning was confirmed by sequencing on all final vectors.

Electrophysiology

Request a detailed protocol

Electrophysiological recordings were made from third-instar larvae at the wandering stage. Larvae were dissected and sharp-electrode recordings were made from muscle 6 in abdominal segments 3 and 4 using an Axoclamp 900 A amplifier (Molecular Devices). The extracellular HL3 saline contained (in mM): 70 NaCl, 5 KCl, 10 MgCl2, 10 Na-HEPES (N-2-hydroxyethylpiperazine-N'-2-ethanesulfonic acid), 115 sucrose, 5 trehalose, 5 HEPES, 1.5 CaCl2. To induce PHP, larvae were incubated with 20 μM PhTX-433 (Santa Cruz Biotechnology) for 10 min at room temperature after partial dissection (see Frank et al., 2006). AP-evoked EPSCs were induced by stimulating hemi-segmental nerves with single APs (0.3-ms stimulus duration, 0.3 Hz), and recorded with a combination of a HS-9A × 10 and a HS-9A × 0.1 headstage (Molecular Devices) in two-electrode voltage clamp mode. mEPSPs and mEPSCs were recorded with one or two HS-9A × 0.1 headstage(s) (Molecular Devices), respectively. Muscle cells were clamped to a membrane potential of −65 mV for EPSC and −100 mV for mEPSC recordings to increase the signal-to-noise ratio.

A total of 50 EPSCs were averaged to obtain the mean EPSC amplitude for each NMJ. mEPSCs and EPSCs were recorded in different NMJs because different headstage combinations were used to improve the signal-to-noise-ratio for mEPSC recordings. Hence, quantal content was calculated by dividing the mean EPSC amplitude of each NMJ by the average of the average mEPSC amplitude of all NMJs of a given experimental group. RRP size was estimated by the method of cumulative EPSC amplitudes (Schneggenburger et al., 1999). NMJs were stimulated with 60 Hz trains (60 stimuli, 5 trains per cell), and the cumulative EPSC amplitude was obtained by back-extrapolating a linear fit to the last 15 cumulative EPSC amplitude values of the 60 Hz train to time zero. The cumulative EPSC amplitude of each NMJ was then divided by the average mEPSC amplitude of all NMJs of a given experimental group to obtain the RRP estimate.

Immunohistochemistry and microscopy

Drosophila NMJ

Request a detailed protocol

Third-instar larval preparations were fixed for 3 min with Bouin’s fixative (100%, Sigma-Aldrich) for confocal microscopy, or ice-cold ethanol (100%, Merck) for 10 min for confocal/STED microscopy. Preparations were washed thoroughly with phosphate-buffered saline (PBS) containing 0.1% Triton X-100 (PBST). After washing, preparations were blocked with 3% normal goat serum in PBST. Incubation with the primary antibody was done at 4°C on a rotating platform overnight. The following antibodies and dilutions were used for NMJ stainings: (Primary) anti-Bruchpilot (nc82, mouse, DSHB, 1:100), anti-GFP (rabbit, Thermo Fisher Scientific, 1:500), anti-GFP (mouse, Thermo Fisher Scientific, 1:500), anti-DsRed (mouse, Santa Cruz Biotechnology, 1:500), anti-SYNORF1 (Synapsin, 3C11, mouse, DSHB, 1:250), anti-Thin (guinea pig, gift from Erika R. Geisbrecht, 1:200), and anti-HRP Alexa-Fluor 647 (goat, Jackson ImmunoResearch, 1:200). For confocal microscopy, Alexa-Fluor anti-mouse 488 (Thermo Fisher Scientific; 1:500) and Alexa Fluor anti-guinea pig 555 (Thermo Fisher Scientific; 1:400) were applied overnight at 4°C on a rotating platform. For gSTED microscopy, the following secondary antibodies (1:100) were applied for 2 hr at room temperature (RT) on a rotating platform: Atto 594 (anti-mouse, Sigma-Aldrich) and Abberior STAR 635P (anti-rabbit, Abberior). Experimental groups of a given experiment were processed in parallel in the same tube. Preparations were mounted onto slides with ProLong Gold (Thermo Fisher Scientific).

S2 cell culture

Request a detailed protocol

S2 cells grown on coverslips were washed with PBST and fixed with 10% PFA (paraformaldehyde) for 10 min. After washing three times with PBST, preparations were blocked with 5% normal goat serum in PBST for 30 min. Incubation with primary antibodies was done at RT on a rotating platform for 2 hr. The following antibodies were used for S2 cell stainings: anti-thin (guinea pig, gift from Erika R. Geisbrecht, 1:400), anti-Dysbindin (mouse, gift from Dion Dickman, 1:400). After washing three times with PBST, cells were incubated with the secondary antibodies Alexa Fluor anti-guinea pig 555 and Alexa Fluor anti-mouse 488 (Thermo Fisher Scientific; both 1:400) at RT on a rotating platform for 2 hr. Cover slips were mounted onto slides with ProLong Gold (Thermo Fisher Scientific) after three PBST washes.

Confocal and gSTED microscopy

Request a detailed protocol

Images were acquired with an inverse Leica TCS SP8 STED 3× microscope (Leica Microsystems, Germany) of the University of Zurich Center for Microscopy and Image Analysis. Excitation light (580 or 640 nm) of a flexible white light laser was focused onto the specimen using a 100× objective (HC PL APO 1.40 NA Oil STED WHITE; Leica Microsystems, Germany) with immersion oil conforming to ISO 8036 with a diffraction index of n = 1.5180 (Leica Microsystems, Germany). For gSTED imaging, the flexible white light laser was combined with a 775 nm STED depletion laser. Emitted light was detected with two HyD detectors in photon counting mode (Leica Microsystems, Germany). Pixel size was 20 × 20 nm and z-stacks were acquired with a step size of 120 nm. For STED imaging, we used time-gated single photon detection (empirical adjustment within a fluorescence lifetime interval from 0.7 to 6.0 ns). Line accumulation was set to 1 and 6 for confocal and STED imaging, respectively. Images were acquired with Leica Application Suite X software (Leica Application Suite X, version 2.0; Leica Microsystems, Germany). Experimental groups were imaged side-by-side with identical settings.

Images were processed and deconvolved with Huygens Professional (Huygens compute engine 17.04, Scientific Volume Imaging B.V., Netherlands). In brief, the ‘automatic background detection’ tool (radius = 0.7 µm), and the ‘auto stabilize’ feature were used to correct for background and lateral drift. Images were deconvolved using the Good’s roughness Maximum Likelihood algorithm with default parameter settings (maximum iterations: 10; signal-to-noise ratio: 7 for STED and 15 for confocal; quality threshold: 0.003).

Western blot

Request a detailed protocol

Transfected cells in 12-well plates were harvested after 72 hr, washed with PBS and lysed by adding 50 µl of RIPA buffer (50 mM Tris, pH 8.0, 150 mM NaCl, 1% Nonidet P-40, 0.5% deoxycholate, 0.1% sodium dodecyl sulfate (SDS), 0.4 mM EDTA (ethylenediaminetetraacetic acid), 10% glycerol) containing protease inhibitors (cOmplete, Mini, EDTA-free Protease Inhibitor Cocktail, Sigma-Aldrich) for 30 min on ice. The lysates were sonified three times for 1 min and boiled for 5 min in SDS-sample buffer containing 5% β-mercaptoethanol. Samples were separated on acrylamide gels using SDS–polyacrylamide gel electrophoresis (PAGE), then transferred to nitrocellulose membranes (Amersham Hibond GE Healthcare). After blocking in 5% milk in PBST for 1 hr, membranes were incubated in the following primary antibodies: anti-GFP (rabbit, Thermo Fisher Scientific, 1:1000), anti-HA (mouse, Biolegend, 1:1000), and anti-Tubulin (E7, mouse, DSHB, 1:1000) in blocking solution overnight. Horseradish peroxidase-conjugated secondary antibodies (anti-mouse-HRP and anti-rabbit-HRP, 1:2000 in blocking solution) were applied to membranes for 2 hr. Detection was performed using ECL Reagent (GE Healthcare, Chicago, IL, USA). Western blots were revealed using enhanced chemiluminescence and imaged using a Fusion FX7 system (Vilber Lourmat). Densitometric analyses (mean pixel intensity of a ROI containing a band of interest) were done in Fiji/ImageJ.

Data analysis

Electrophysiology

Request a detailed protocol

Electrophysiology data were acquired with Clampex (Axon CNS, Molecular Devices) and analyzed with custom-written routines in Igor Pro (Wavemetrics). For the genetic screen data, mEPSPs were detected with a template matching algorithm implemented in Neuromatic (Rothman & Silver, 2018) running in Igor Pro (Wavemetrics). The average mEPSP amplitude was calculated from all detected events in a recording after visual inspection for false positives. For the remaining data, mEPSC data were analyzed using routines written with scientific python libraries, including numpy, scipy, IPython and neo (Garcia et al., 2014), and mEPSCs were detected using an implementation of a template-matching algorithm (Clements and Bekkers, 1997).

NMJ morphology

Request a detailed protocol

Microscopy images were analyzed using custom-written routines in ImageJ/Fiji (version 1.51n, National Institutes of Health, USA). Brp quantification was performed as follows: First, individual Brp puncta were isolated by segmenting binary fluorescence intensity threshold masks (15% or 35% of the maximum intensity value) of background corrected (rolling ball, radius = 1 μm) and filtered (3 × 3 median) maximum intensity projection images. The number of Brp objects in the mask served as a proxy for AZ number and was normalized to the area of the HRP mask (binary mask, 15% or 35% of the maximum intensity value). Average Brp-intensity values were calculated for each Brp punctum from background-corrected, unfiltered maximum intensity projection images.

NND analysis

Request a detailed protocol

For the NND analysis (Figure 5), individual synaptic boutons were segmented manually within a deconvolved gSTED stack and a single plane in the middle of the bouton was extracted for further analysis. Next, Fiji’s ‘Find Maxima’ algorithm was used to obtain the x,y coordinate of the brightest pixel within each Dysbindinvenus and ThinmCherry punctum. For the maximum of each Dysbindin punctum, the distances to the maxima of all Thin puncta within the same bouton were measured and the NNDs were calculated. For each bouton, the analysis was repeated after assigning random x,y coordinates to each Dysbindin and Thin punctum within the bouton boundaries using the Python package Shapely (Gillies and others, 2007; https://github.com/shapely/shapely). NND values were averaged for each bouton.

Correlation analysis S2 cells

Request a detailed protocol

Pearson’s correlation coefficients (r) were calculated for each pixel in single confocal planes of Drosophila S2 cells coexpressing Dysbindinvenus and ThinmCherry using Costes’ approach (Costes et al., 2004) implemented in the JACoP toolbox of ImageJ/Fiji (Bolte and Cordelières, 2006; Figure 5—figure supplement 2B). The algorithm also creates simulated images by randomly sampling point spread function-sized chunks of the original image, and calculating r for each pixel of the simulated data.

Statistics

Statistical analyses were done using RStudio Team (2021). RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA, http://www.rstudio.com/. For more than two factors, we used two-way analysis of variance (ANOVA) followed by Tukey’s post hoc test to correct for multiple comparisons between genotypes and conditions. For one factor with more than two groups, one-way ANOVA with Tukey’s multiple comparisons was performed. Two-sided Student’s t-tests or nonparametric Mann–Whitney U-tests were used for comparison between two groups after a Shapiro–Wilk test and a Levene’s test. Statistical significance (p) was set to 0.05 (*), 0.01 (**), and 0.001 (***). Power analysis was performed using the pwr-package of Rstudio. Minimum desired effect size based on Cohen’s d value was used to estimate the minimum sample size for a power ≥0.8 and a significance level of 0.05 for two-sided Student’s t-tests or Mann–Whitney U-tests. Data are given as mean ± standard error of the mean (SEM).

Figures were assembled using GIMP (The GIMP team, 2.8.10, https://www.gimp.org/), Inkscape (Inkscape project, 0.92.2. http://www.inkscape.org), and Affinity Designer (1.10.4, Serif (Europe) Ltd, West Bridgford, Nottinghamshire, United Kingdom).

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1-6.

References

Decision letter

  1. Nils Brose
    Reviewing Editor; Max Planck Institute of Experimental Medicine, Germany
  2. Lu Chen
    Senior Editor; Stanford University, United States
  3. Hiroshi Kawabe
    Reviewer; Gunma University, Japan
  4. Eckart D Gundelfinger
    Reviewer; Leibniz Institute for Neurobiology, Magdeburg, Germany, Germany

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Lu Chen as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Hiroshi Kawabe (Reviewer #1); Eckart D Gundelfinger (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission. There is consensus that your paper is a very strong eLife candidate, provided that the reviewers' comments can be addressed. Four items require additional data or experiments (see below).

Recommendations for the Authors

A. Revisions Requiring Additional Experiments

A1. Because global loss of Thin impairs muscle development, the authors re-express Thin solely in the muscle to study synaptic morphology in the absence of presynaptic thin (Figure 5). They find that in this situation presynaptic AZ numbers are significantly increased. The authors attribute this phenotype to unphysiological Thin levels in the muscle rather than to a loss of presynaptic Thin, because postsynaptic Thin overexpression in wild-type animals also increases AZ numbers. This attribution is not fully justifiable without additional data. The precise interpretation of the morphological phenotypes found is important to define the processes that are controlled by Thin. To clarify the issue the authors should analyse NMJ morphology upon presynaptically driven Thin-RNAi as used in the corresponding functional measurements (Figure 4).

A2. Thin was included in the screen in the form of a homozygous mutant allele (∆A) that was previously described to severely affect muscle integrity. As the authors admit, the corresponding reduced miniature amplitudes may confound conclusions – in particular as the QC is increased compared to control. This might imply that the mutant displays some capacity for homeostatic upregulation, at least on a long-term scale. However, Figure 3 shows that such a capacity is not apparent in the absence GluRIIA and that loss of Thin does not further reduce mini amplitudes when GluRIIA is missing. This leaves the reader puzzled without further information, especially on GluRII(A) abundance. It is only with Figure 4 that a motoneuronal RNAi is introduced, importantly with no discernible postsynaptic deficits. It is used to show that an increased RRP underlies increased baseline transmission, whereas SV release probability remains unchanged. The reviewers recommend to introduce this issue earlier (preferentially before Figure 3, which might actually become a supplementary figure) and to further elaborate to address short-term PHP deficits by performing PhTx experiments. Also, the morphological features (mainly Brp, as in Figure 5, maybe in combination with a SV marker) should be explored to increase comparability of the experiments.

A3. Based on the data provided, (partial) co-localization of Dysbindin and Thin at NMJs can only be deduced based on overexpression of fluorescently tagged proteins in motoneurons (Figure 6). This is a substantial shortcoming – but it is probably not easily overcome. Hence, it is important to verify that the two proteins affect each other. In S2 cells, overexpression of Dysbindin in S2 cells leads to striking recruitment of endogenous Thin to the periphery, actually to the very same hot spots (Figure 6). Here, controls are required to rule out that there are any 'bleed-through' effects (here from the green into the magenta channel), and a quantitative image analysis should be carried out. This could, in the best case, make a co-immunoprecipitation dispensable. Beyond this, the authors should explore the possibility of using a similar approach at NMJs instead of in S2 cells, comparing overexpression of tagged versions of Dysbindin alone and Thin alone vs. Dysbindin and Thin co-expressed, e.g. with using Synapsin (or Brp) as localization reference.

A4. It appears very important to test whether Dysbindin expression increases in the absence of Thin, possibly to an extent that endogenous protein becomes directly detectable by an antibody.

B. Revisions Requiring Further Data Analysis, Text Redaction, or Consideration

B1. The mammalian TRIM family is composed of dozens of members. The authors should provide a comparative domain and amino acid sequence analysis to support the notion that Thin is the TRIM32 ortholog. Corresponding sequence analyses could also serve as a basis to discuss related proteins in the fly and possible functional redundancies.

B2. As mentioned in the manuscript and shown by others, presynaptic Dysbindin overexpression increases neurotransmitter release. This is consistent with the model put forward in the current manuscript. Related to increased AZ numbers observed (Figure 5), which the authors do not attribute to loss of presynaptic Thin, the questions arises as to whether presynaptic Dysbindin overexpression increases AZ numbers. If this were not the case, it would support the authors' model, where the Thin-Dysbindin interaction influences synaptic strength at the level of an individual synapse. If the authors already have data related to this issue, they should be included.

B3. The statement that distinct Thin and Dysbindin spots partially overlap is based on nice, high-resolution STED images. However, in terms of quantification the authors only show a single line profile. A more quantitative correlation analysis would strengthen the conclusion and improve the manuscript.

B4. The authors argue that presynaptic Thin remains hardly detectable because of the dominant expression in muscles. The question arises as to whether staining of NMJs in animals with muscle-specific Thin RNAi might overcome this issue and provide information on presynaptic Thin.

B5. The question arises whether there is an observable effect of PhTX treatment on the level of tagged Dysbindin that can be addressed by live imaging.

B6. The cumulative evidence indicates that under baseline conditions, Thin limits SV release via control of Dysbindin (Figure 7). Given that the screen identified quite a few E3 ligases, the question arises as to whether there are candidates in the screen that could be included as example where PHP is affected independently of Dysbindin.

B7. The authors' measure of release probability (Pr) is related to the estimated RRP size, which should be treated with care (see e.g. Neher, Merits and limitations of vesicle pool models in view of heterogeneous populations of synaptic vesicles, Neuron, 2015). For an additional and independent assessment of Pr, the authors should quantify the ratio of 1st and 2nd EPSCs in the 60 Hz trains.

C. Other Issues Requiring Attention

C1. The exact genotypes of all of the Drosophila lines used in this study need to be listed in a clear and comprehensive fashion to provide this important information to the reader – analogous to or in Table S1. Ideally, the red colour code of genes in Figure 1E could be used for this new information and for the 'old' Table S1.

C2. Flybase lists 5 publicly available Thin-specific RNAi lines (3 at Bloomington, 2 at VDRC), but the line that was used here seems not to have been specified. This should be rectified. The authors should explain why the specific line was used and whether the use of alternative RNAi lines was considered to validate the observed phenotype and rule out off-target effects.

C3. For the sake of consistency, the genotype thinΔA; 24BGal4>UAS-thin should either be consistently referred to as 'postsynaptic rescue' (Figure 2) or as 'presynaptic thinΔA mutant' (Figure 5) throughout the manuscript.

C4. The reviewers noticed inconsistencies in the methods section concerning cloning experiments. The mCherry-tagged Thin construct is once referred to as "pUAS_attB_mCherry_thin vector" in the paragraph on plasmid construction, but as "pUAS-thin-mCherry" in the previous paragraph, and as "UAS-thinmcherry" in the Results section. The construct descriptor should be consistent throughout the manuscript. Brief inspection of the primer sequences indicates that mCherry was fused to the C-terminus of Thin, but the restriction sites within the primers do not all match the enzymes that are named as the ones used for cloning. Finally, the authors should indicate which of the Thin splice variants was expressed from the UAS transgene.

C5. The reviewers noted possible inconsistencies in Figure 2. In the top right set of example traces in Figure 2A, the large pink and red traces show a clear difference, which is reflected in the second set of bar diagrams in Figure 2C (i.e. pink and red bars). On the other hand, sky-blue and blue traces on the bottom left in Figure 2A show no difference while the third set of bar diagrams in Figure 2C (i.e. sky blue and blue bars) show a significant difference. This should be explained. In the experiments shown in Figure 4, the authors knocked down Thin in the presynaptic neuron with an intact expression in postsynaptic muscle cells. In Figure 4C, it is shown that this treatment increases EPSCs. This scenario is similar to that in the Thin KO with postsynaptic rescue, shown in Figure 2C (light green bar). However, no difference between gray and light green bars in Figure 2C is apparent. It is unclear how this can be explained.

C6. Figure 5 and Figure S2 indicate striking changes regarding the AZ protein Brp that occur alongside postsynaptic expression of Thin, regardless of WT or mutant background. This might imply an interesting 'retrograde' effects. It might be a good idea to provide a comment on this finding. Further, it seems that at least the Brp labellings in Figure 5 do not at all reflect the different intensities shown in the corresponding graphs. This needs to be explained or other images should be chosen.

C7. The reviewers interpret the images in Figure 6A-6D to originate from mcherry and venus. If so, they should be indicated as such i.e. "Thin-mcherry" and "Dysb-venus" in panels A-D. Otherwise, the reader might assume that endogenous untagged proteins are shown.

C8. There are shortcomings in the documentation of the biochemical part of the cell culture experiments. The Western Blot in Figure 6E is not labelled properly (band at 25 kDa in bottom panel), the bands shown do not really match the data in the bar graph in Figure 6F (e.g. the thin2x sample), and it is unclear what normalization and loading control were used (requires MEMCode or housekeeping protein quantification), and what type of tissue samples from exactly what genotypes were loaded. This should be rectified. Further, there is a faint band at >50 kDa in all lanes of the upper panel of Figure 6E, even in the thin2x lane. This should be discussed. The legend should note that Dysb-Venus was detected with anti-GFP antibodies. The expression level of Thin appears to have been assessed only by the concentration of the transfected DNA rather than by blot analysis or at least determining the actual rate of transfected cells. If true, this should be stated. Further, the methods section mentions that Thin-mCherry was used for transfection and anti-DsRed antibody for detection on blots, but no corresponding results are described.

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

Thank you for resubmitting your work entitled "The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression" for further consideration by eLife. Your revised article has been evaluated by Lu Chen (Senior Editor) and a Reviewing Editor.

The manuscript has been improved very substantially. No further experiments are required, but there are five remaining issues that need to be addressed by changes to the manuscript, as outlined below:

1. The authors state in their rebuttal that "Under baseline conditions, i.e. in the absence of PhTX, the miniature amplitude was decreased in thinΔA mutants (Figure 2B), after presynaptic and postsynaptic rescue (Figure 2B)". However, in Figure 2B, the gray and light red bars show significant differences, while gray and light blue/light green bars do not. This indicates that mEPSC amplitudes were NOT decreased in thinΔA mutants upon presynaptic or postsynaptic rescue. Can this be clarified or is there an underlying asterisk labeling error? The latter, if relevant, might warrant a final detailed check of the entire manuscript.

2. Demonstrating an increase in Dysbindin levels in thin mutants is important. Many reports have demonstrated reduced expression of alleged "substrates" upon overexpression of a corresponding E3 – as shown in Figure 5. Figure S2C. However, such results have limited value. Overexpression of an E3 can cause artificial ubiquitination by excess enzyme binding with low-affinity to proteins that are not endogenous substrates. Since it is not difficult to detect Dysbindin-Venus by Western blotting, the best experiment under the current circumstances might be to study thin mutant flys expressing low levels of Dysbindin-Venus. At this juncture, the reviewers do not require this experiment to be done. Instead, the authors should conservatively rephrase their conclusion that Dysbindin is regulated by the UPS in a Thin-dependent manner (Figure 6F) and might eliminate "26S" from Figure 6F and change the text accordingly.

3. There appears to be a misunderstanding regarding the reviewers' comment C5 – the concerns regarding discrepancies between Figure 2C and Figure 4C. In the reviewers' view, the expression of thin should be the same in these two scenarios; no thin expression in presynapse but intact expression in postsynapse. There should not be any difference between the results in Figure 2C and Figure 4C. This issue should be explained and resolved.

4. The identity of the transgenic lines shown in Figure 1E should be disclosed. The authors have done a good job of listing all genotypes. However, in its present form, the assignment of individual genotypes to data points on the volcano plot cannot be clearly extracted from the supplementary table. As a compromise, the authors could use the red colour code in the table as previously suggested (comment C1).

5. To avoid word repetition, the reviewers suggest slightly rephrasing the sentence "Regarding the decrease in Brp intensity, Brp intensity was decreased…" (lines 230-231).

https://doi.org/10.7554/eLife.71437.sa1

Author response

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission. There is consensus that your paper is a very strong eLife candidate, provided that the reviewers' comments can be addressed. Four items require additional data or experiments (see below).

Recommendations for the Authors

A. Revisions Requiring Additional Experiments

A1. Because global loss of Thin impairs muscle development, the authors re-express Thin solely in the muscle to study synaptic morphology in the absence of presynaptic thin (Figure 5). They find that in this situation presynaptic AZ numbers are significantly increased. The authors attribute this phenotype to unphysiological Thin levels in the muscle rather than to a loss of presynaptic Thin, because postsynaptic Thin overexpression in wild-type animals also increases AZ numbers. This attribution is not fully justifiable without additional data. The precise interpretation of the morphological phenotypes found is important to define the processes that are controlled by Thin. To clarify the issue the authors should analyse NMJ morphology upon presynaptically driven Thin-RNAi as used in the corresponding functional measurements (Figure 4).

We fully agree. As suggested, we investigated presynaptic NMJ morphology after presynaptic thin-RNAi expression. In addition, we examined NMJ morphology in homozygous thinΔA mutants. While we observed a slight increase in Brp number after presynaptic thin-RNAi expression (new Figure 4—figure supplement 1), Brp number and NMJ area were unchanged in thinΔA mutants (new Figure 3). The observation of largely unchanged NMJ area and Brp number in thin null mutants (new Figure 3), which display a complete PHP block and increased presynaptic release (Figure 2), provides strong genetic evidence that the defects in synaptic physiology are unlikely a consequence of increased NMJ size or AZ number. Conversely, PHP and baseline synaptic transmission were unaffected at NMJs with increased NMJ area and Brp number after postsynaptic thin expression in wild type (new Figure 3—figure supplement 1). Thus, although we cannot exclude that the changes in NMJ size or AZ number seen after postsynaptic thin rescue or presynaptic thin-RNAi expression contribute to the changes in synaptic physiology, our data suggest that the changes in NMJ area and AZ number are separable from changes in synaptic physiology. We updated the Results and Discussion sections correspondingly. => See Results (l. 209), and Discussion (l. 389).

A2. Thin was included in the screen in the form of a homozygous mutant allele (∆A) that was previously described to severely affect muscle integrity. As the authors admit, the corresponding reduced miniature amplitudes may confound conclusions – in particular as the QC is increased compared to control. This might imply that the mutant displays some capacity for homeostatic upregulation, at least on a long-term scale. However, Figure 3 shows that such a capacity is not apparent in the absence GluRIIA and that loss of Thin does not further reduce mini amplitudes when GluRIIA is missing. This leaves the reader puzzled without further information, especially on GluRII(A) abundance. It is only with Figure 4 that a motoneuronal RNAi is introduced, importantly with no discernible postsynaptic deficits. It is used to show that an increased RRP underlies increased baseline transmission, whereas SV release probability remains unchanged. The reviewers recommend to introduce this issue earlier (preferentially before Figure 3, which might actually become a supplementary figure) and to further elaborate to address short-term PHP deficits by performing PhTx experiments. Also, the morphological features (mainly Brp, as in Figure 5, maybe in combination with a SV marker) should be explored to increase comparability of the experiments.

As recommended, we investigated PHP after presynaptic thin-RNAi expression and observed a complete PHP block (Figure 4—figure supplement 1), consistent with the thinΔA mutant data (Figure 2). Furthermore, we probed Brp and NMJ morphology after presynaptic thin-RNAi expression (see A1, Figure 4—figure supplement 1).

Regarding the reduced miniature amplitude in thinΔA mutants: Under baseline conditions, i.e. in the absence of PhTX, miniature amplitude was decreased in thinΔA mutants (Figure 2B), after presynaptic and postsynaptic rescue (Figure 2B), and largely unchanged upon presynaptic thin-RNAi expression (Figure 4B). Quantal content was increased in thinΔA mutants (Figure 2E), after postsynaptic rescue (Figure 2E), and after presynaptic thin-RNAi expression (Figure 4D). Together, these data imply that the increase in quantal content under baseline conditions induced by presynaptic thin manipulations is separable from a decrease in miniature amplitude.

By definition, PHP is induced by a relative decrease in miniature amplitude. Given that quantal content increased after presynaptic thin manipulations independent of changes in miniature amplitude (see last paragraph), we consider it unlikely that the increased quantal content under baseline conditions represents a homeostatic response.

Miniature amplitude was decreased in thinΔA-GluRIIA double mutants compared to thinΔA mutants (Figure 2—figure supplement 1B). While a decrease in miniature amplitude induced an increase in quantal content in GluRIIA mutants compared to WT (Figure 2—figure supplement 1D), there was no increase in quantal content in thinΔA-GluRIIA double mutants compared to thinΔA mutants (Figure 2— figure supplement 1D), implying a PHP defect.

Indeed, miniature amplitude was similar between GluRIIA mutants and thinΔAGluRIIA double mutants (Figure 2—figure supplement 1B). This observation either indicates that we could not resolve a further decrease in miniature amplitude because of signal-to-noise limitations, or that loss of thin reduces GluR levels. Importantly, while miniature amplitudes were similar between GluRIIA mutants and thinΔA-GluRIIA double mutants (Figure 2—figure supplement 1B), EPSC amplitudes were decreased in thinΔA-GluRIIA double mutants, but not in GluRIIA mutants (Figure 2—figure supplement 1C). This suggests a thin-dependent decrease in EPSC amplitude in the GluRIIA mutant background, consistent with impaired PHP.

We summarized and discussed these points in the Discussion (l. 428) and the legend of Figure 2—figure supplement 1.

As suggested, we now show the GluRIIA data as a supplementary figure (Figure 2—figure supplement 1). Based on the fact that we now quantified NMJ morphology in thinΔA mutants (Figure 3, A1), and that we carried out the formal genetic analysis with presynaptic and postsynaptic rescue in the thinΔA mutant background (Figure 2), we decided showing the morphology data for thinΔA mutants and rescue experiments (new Figure 3) before introducing the thin-RNAi physiology and morphology data (Figure 4 and Figure 4—figure supplement 1).

A3. Based on the data provided, (partial) co-localization of Dysbindin and Thin at NMJs can only be deduced based on overexpression of fluorescently tagged proteins in motoneurons (Figure 6). This is a substantial shortcoming – but it is probably not easily overcome. Hence, it is important to verify that the two proteins affect each other. In S2 cells, overexpression of Dysbindin in S2 cells leads to striking recruitment of endogenous Thin to the periphery, actually to the very same hot spots (Figure 6). Here, controls are required to rule out that there are any 'bleed-through' effects (here from the green into the magenta channel), and a quantitative image analysis should be carried out. This could, in the best case, make a co-immunoprecipitation dispensable. Beyond this, the authors should explore the possibility of using a similar approach at NMJs instead of in S2 cells, comparing overexpression of tagged versions of Dysbindin alone and Thin alone vs. Dysbindin and Thin co-expressed, e.g. with using Synapsin (or Brp) as localization reference.

We performed additional experiments and analyses regarding the relationship between Thin and Dysbindin localization in S2 cells and at the NMJ. As recommended, we first investigated a potential bleed-through between the Dysbindin and Thin channel in S2 cells: To test whether the Thin channel (magenta) is excited by the Dysbindin channel (green), we only expressed dysbindin in S2 cells and imaged both channels. Fluorescence intensity did not significantly deviate from background in the Thin channel (magenta) (Figure 5—figure supplement 2A), suggesting no major bleed through from the Dysbindin to the Thin channel. It is also worth noting that both channels were imaged sequentially when expressing both, dysbindin and thin (Figure 5—figure supplement 2A). Finally, although tightly correlated, we also observed a small fraction of uncorrelated Dysbindin and Thin fluorescence (Figure 5—figure supplement 2A). Hence, we consider a major contribution of channel crosstalk to the Dysbindin and Thin localization data in S2 cells unlikely.

Next, we quantified the Pearson’s correlation coefficient (r) for Thin and

Dysbindin fluorescence intensity per pixel in S2 cells and found an average r=0.84

(Figure 5—figure supplement 2B), significantly higher than expected from random Thin and Dysbindin localizations simulated by sampling random point spread function-sized chunks of the data (Figure 5—figure supplement 2B and Material and Methods).

Finally, we studied the relationship between Thin and Dysbindin localization at the NMJ by quantifying the nearest-neighbor distances (NNDs) between Thin and Dysbindin puncta at STED resolution upon overexpression (Figure 5). This analysis revealed significantly smaller NNDs between Thin and Dysbindin puncta compared to simulated random localizations within NMJ boutons (Figure 5). Collectively, these data suggest a relationship between Thin and Dysbindin localization in S2 cells and at the NMJ.

Additionally, we probed Dysbindin localization after overexpression with regard to Synapsin localization at the NMJ of wild type and thinΔA mutants using STED microscopy. Although we revealed a slight, but significant decrease in NND between Dysbindin and Synapsin puncta in thinΔA mutants compared to wild type, we also detected a slight increase in Synapsin puncta density in thinΔA mutants, thereby complicating the interpretation of the results of this experiment. We therefore decided against including these data into the manuscript.

A4. It appears very important to test whether Dysbindin expression increases in the absence of Thin, possibly to an extent that endogenous protein becomes directly detectable by an antibody.

We now performed an anti-dysbindin staining in the thinΔA mutant background. Unfortunately, we failed to detect a significant anti-dysbindin signal over background fluorescence in thinΔA mutants. It is worth noting that we quite commonly fail in detecting proteins with low endogenous levels by immunohistochemistry at the Drosophila NMJ.

B. Revisions Requiring Further Data Analysis, Text Redaction, or Consideration

B1. The mammalian TRIM family is composed of dozens of members. The authors should provide a comparative domain and amino acid sequence analysis to support the notion that Thin is the TRIM32 ortholog. Corresponding sequence analyses could also serve as a basis to discuss related proteins in the fly and possible functional redundancies.

We carried out a comparative domain and amino acid sequence analysis between Thin and the human TRIM family (Figure 1—figure supplement 2). Consistent with previous work (LaBeau-DiMenna et al., 2012), this analysis suggests that TRIM32 likely represents the closest human ortholog of thin. In short, out of the large TRIM family, TRIM32 is the only TRIM that has a domain composition that is similar to the one of Thin (N-terminal TRIM followed by C-terminal NHL repeats; Figure 1—figure supplement 2A). Moreover, amino acid sequence alignment of Thin’s RING domains and NHL domains revealed evolutionary conservation of both domains compared to TRIM32, as well as other members of the TRIM C-VII family, which also contains TRIM32 (Ozato et al., 2008; Figure 1—figure supplement 2B). Together, this analysis supports the idea that TRIM32 is Thin’s closest human ortholog.

We updated the manuscript accordingly (l. 142, Figure 1—figure supplement 2).

B2. As mentioned in the manuscript and shown by others, presynaptic Dysbindin overexpression increases neurotransmitter release. This is consistent with the model put forward in the current manuscript. Related to increased AZ numbers observed (Figure 5), which the authors do not attribute to loss of presynaptic Thin, the questions arises as to whether presynaptic Dysbindin overexpression increases AZ numbers. If this were not the case, it would support the authors' model, where the Thin-Dysbindin interaction influences synaptic strength at the level of an individual synapse. If the authors already have data related to this issue, they should be included.

Based on your suggestion, we probed Brp number and NMJ morphology after dysbindin overexpression. This analysis did not yield differences in Brp number or NMJ area compared to controls (Figure 5—figure supplement 1F), thereby further supporting the notion that changes in AZ number/NMJ size are separable from changes in synaptic physiology (see also A1).

B3. The statement that distinct Thin and Dysbindin spots partially overlap is based on nice, high-resolution STED images. However, in terms of quantification the authors only show a single line profile. A more quantitative correlation analysis would strengthen the conclusion and improve the manuscript.

We now quantified the nearest-neighbor distances (NNDs) between Thin and Dysbindin puncta at STED resolution upon overexpression (Figure 5) and observed significantly smaller NNDs between Thin and Dysbindin puncta compared to randomly distributed puncta (Figure 5, see also A3). Note that we decided against conducting a fluorescence intensity-based correlation analysis, because the comparably low fluorescence intensity of STED data has a rather small dynamic range, thus complicating a correlation analysis.

B4. The authors argue that presynaptic Thin remains hardly detectable because of the dominant expression in muscles. The question arises as to whether staining of NMJs in animals with muscle-specific Thin RNAi might overcome this issue and provide information on presynaptic Thin.

Based on this suggestion, we probed endogenous Thin localization in relation to Brp in WT and thinΔA mutants and observed anti-thin fluorescence in close proximity to Brp in WT, but not in thinΔA mutants (Figure 5—figure supplement 1D, E). These data suggest that endogenous Thin localizes to presynaptic boutons in addition to postsynaptic muscle cells. We did not repeat these experiments after muscle-specific RNAi expression due to time reasons (l. 292).

B5. The question arises whether there is an observable effect of PhTX treatment on the level of tagged Dysbindin that can be addressed by live imaging.

We conducted this experiment but did not detect obvious differences in anti-GFP fluorescence intensity or localization after venus-dysbindin overexpression between PhTX-treated and untreated NMJs (not shown).

B6. The cumulative evidence indicates that under baseline conditions, Thin limits SV release via control of Dysbindin (Figure 7). Given that the screen identified quite a few E3 ligases, the question arises as to whether there are candidates in the screen that could be included as example where PHP is affected independently of Dysbindin.

Incorporation of other candidate genes identified by the genetic screen would presuppose a rather elaborate set of experiments (genetic rescue, morphology, relationship to dysbindin etc.), similar to the one presented for thin in the present study. The realization of these experiments was not feasible during the revision.

B7. The authors' measure of release probability (Pr) is related to the estimated RRP size, which should be treated with care (see e.g. Neher, Merits and limitations of vesicle pool models in view of heterogeneous populations of synaptic vesicles, Neuron, 2015). For an additional and independent assessment of Pr, the authors should quantify the ratio of 1st and 2nd EPSCs in the 60 Hz trains.

We now analyzed the paired-pulse ratio (PPR) of the first two EPSC amplitudes of the 60-Hz train. There was a slight increase in PPR after presynaptic thin-RNAi expression compared to controls (Figure 4H), implying a slight decrease in release probability (pr). By contrast, the train-based pr estimate (first EPSC amplitude/ cum. EPSC amplitude) was similar between thin-RNAi and controls (Figure 4G). Together, these data suggest that the increase in presynaptic release upon presynaptic thinRNAi expression is unlikely caused by an increase in pr, and that presynaptic thinRNAi expression may even lead to a slight pr decrease. We updated the Results section accordingly (l. 263).

C. Other Issues Requiring Attention

C1. The exact genotypes of all of the Drosophila lines used in this study need to be listed in a clear and comprehensive fashion to provide this important information to the reader – analogous to or in Table S1. Ideally, the red colour code of genes in Figure 1E could be used for this new information and for the 'old' Table S1.

We updated the manuscript and Table S1 with regard to the exact genotypes (Table S1).

C2. Flybase lists 5 publicly available Thin-specific RNAi lines (3 at Bloomington, 2 at VDRC), but the line that was used here seems not to have been specified. This should be rectified. The authors should explain why the specific line was used and whether the use of alternative RNAi lines was considered to validate the observed phenotype and rule out off-target effects.

We used Bloomington stock 42826 (RRID:BDSC_42826; P{TRiP.HMS02508}attP40). Out of the four stocks available from Bloomington, three express dsRNA for RNAi of thin under UAS control in the pVALIUM20 vector, one of the second-generation TRiP knockdown vectors (Ni et al., 2011; Perkins et al., 2015). The other line available from Bloomington was made with the older, firstgeneration pVALIUM1 vector. Out of the three VALIUM20 stocks available, we used stock 42826, because it is the only one that was previously published in the context of genetic screens (Kuleesha et al., 2016, Rotelli et al., 2019). We neither ordered nor tested additional thin RNAi lines from Bloomington or VDRC because of time reasons. We updated the methods section correspondingly (Key resources table, an l. 482).

C3. For the sake of consistency, the genotype thin ΔA; 24BGal4>UAS-thin should either be consistently referred to as 'postsynaptic rescue' (Figure 2) or as 'presynaptic thin ΔA mutant' (Figure 5) throughout the manuscript.

We now consistently use the term ‘postsynaptic rescue’ throughout the manuscript.

C4. The reviewers noticed inconsistencies in the methods section concerning cloning experiments. The mCherry-tagged Thin construct is once referred to as "pUAS_attB_mCherry_thin vector" in the paragraph on plasmid construction, but as "pUAS-thin-mCherry" in the previous paragraph, and as "UAS-thinmcherry" in the Results section. The construct descriptor should be consistent throughout the manuscript. Brief inspection of the primer sequences indicates that mCherry was fused to the C-terminus of Thin, but the restriction sites within the primers do not all match the enzymes that are named as the ones used for cloning. Finally, the authors should indicate which of the Thin splice variants was expressed from the UAS transgene.

We are sorry about these inconsistencies and now consistently labelled the construct as “pUAS-mCherry-thin”, “ThinmCherry”. Moreover, we added the correct primer sequences and the Ref.Seq number for the expressed Thin isoform (isoform A) to the methods section (Material and Methods, l. 509).

Note that we now performed additional cloning experiments for the new Western blot analysis (see C8).

C5. The reviewers noted possible inconsistencies in Figure 2. In the top right set of example traces in Figure 2A, the large pink and red traces show a clear difference, which is reflected in the second set of bar diagrams in Figure 2C (i.e. pink and red bars). On the other hand, sky-blue and blue traces on the bottom left in Figure 2A show no difference while the third set of bar diagrams in Figure 2C (i.e. sky blue and blue bars) show a significant difference. This should be explained. In the experiments shown in Figure 4, the authors knocked down Thin in the presynaptic neuron with an intact expression in postsynaptic muscle cells. In Figure 4C, it is shown that this treatment increases EPSCs. This scenario is similar to that in the Thin KO with postsynaptic rescue, shown in Figure 2C (light green bar). However, no difference between gray and light green bars in Figure 2C is apparent. It is unclear how this can be explained.

Regarding the representative presynaptic thin rescue data (sky blue and dark blue, Figure 2): We apologize for having chosen a representative cell for the presynaptic rescue group with PhTX (dark blue) that did not reflect the group average and now updated the example trace correspondingly (dark blue traces in Figure 2A). Most likely, the difference in EPSC amplitude between PhTX-treated and untreated cells after presynaptic thin rescue is a result of incomplete rescue, a phenomenon quite frequently observed after overexpression-based genetic rescue at the Drosophila NMJ. Alternatively, the smaller EPSC amplitudes after rescue may arise from defects in muscle architecture (LaBeau-DiMenna et al., 2012). Note, however, that there was a significant increase in quantal content after presynaptic rescue (Figure 2D), suggesting a partial PHP rescue. We now discuss this in the updated Results section (l. 160).

Concerning the comparison of EPSC amplitudes between thinΔA presynaptic rescue (Figure 2C) and presynaptic thin-RNAi (Figure 4C): If we understand the concern correctly, then the question is why the increase in EPSC amplitude after presynaptic thin-RNAi expression (Figure 4C) is more pronounced than the one after postsynaptic rescue (Figure 2C, light green data). The short answer is that this is most likely due to different effects on mEPSC amplitude in these genetic backgrounds: mEPSC amplitudes were decreased in thinΔA (Figure 2B, light red) and – to a lesser extend – after postsynaptic rescue (Figure 2B, light green), but largely unchanged after presynaptic thin-RNAi expression (Figure 4B). In combination with largely unchanged EPSC amplitudes in thinΔA (Figure 2C, light red), slightly increased EPSC amplitudes after postsynaptic rescue (Figure 2C, light green), and increased EPSP amplitudes after presynaptic thin-RNAi expression (Figure 4C), this translates into a similar increase in quantal content in these three genotypes (Figure 2E and 4D). Hence, thin perturbation results in enhanced neurotransmitter release under baseline conditions in three independent experiments.

We discuss the relationship between miniature amplitude and presynaptic release in the Discussion (l. 428).

C6. Figure 5 and Figure S2 indicate striking changes regarding the AZ protein Brp that occur alongside postsynaptic expression of Thin, regardless of WT or mutant background. This might imply an interesting 'retrograde' effects. It might be a good idea to provide a comment on this finding. Further, it seems that at least the Brp labellings in Figure 5 do not at all reflect the different intensities shown in the corresponding graphs. This needs to be explained or other images should be chosen.

Indeed, Brp intensity was decreased in thinΔA mutants, after presynaptic rescue (Figure 3E), and postsynaptic thin overexpression in wild type (new Figure 3—figure supplement 1E). We also observed a trend towards decreased Brp intensity after postsynaptic rescue (Figure 3). However, while Brp intensity was decreased after presynaptic rescue (new Figure 3) and postsynaptic thin overexpression (new Figure 3—figure supplement 1), PHP and baseline synaptic transmission were unchanged in both genotypes (Figure 2, new Figure 3—figure supplement 1). Conversely, Brp levels were unaffected by presynaptic thin-RNAi expression, but PHP was impaired, and baseline synaptic transmission increased (Figure 4, new Figure 4—figure supplement 1). Together, these results again support the idea that changes in NMJ morphology are separable from changes in synaptic physiology after genetic thin manipulations (see A1). Although possible, we therefore consider it unlikely that the decrease in Brp intensity is a major factor underlying the PHP defect or the increase in synaptic transmission after presynaptic thin perturbation.

We now discuss the changes in Brp intensity in the Results (l. 209) and Discussion sections (l. 389).

Finally, we updated the example image in the new version of Figure 3 to better reflect the average Brp data.

C7. The reviewers interpret the images in Figure 6A-6D to originate from mcherry and venus. If so, they should be indicated as such i.e. "Thin-mcherry" and "Dysb-venus" in panels A-D. Otherwise, the reader might assume that endogenous untagged proteins are shown.

We apologize for not specifying the tag in the images. As specified in the figure legend, the images indeed show pUAS-mCherry-thin (‘ThinmCherry’) and pUAS-venusDysbindin (‘Dysbindinvenus’). We updated the new Figure 5 correspondingly.

C8. There are shortcomings in the documentation of the biochemical part of the cell culture experiments. The Western Blot in Figure 6E is not labelled properly (band at 25 kDa in bottom panel), the bands shown do not really match the data in the bar graph in Figure 6F (e.g. the thin2x sample), and it is unclear what normalization and loading control were used (requires MEMCode or housekeeping protein quantification), and what type of tissue samples from exactly what genotypes were loaded. This should be rectified. Further, there is a faint band at >50 kDa in all lanes of the upper panel of Figure 6E, even in the thin2x lane. This should be discussed. The legend should note that Dysb-Venus was detected with anti-GFP antibodies. The expression level of Thin appears to have been assessed only by the concentration of the transfected DNA rather than by blot analysis or at least determining the actual rate of transfected cells. If true, this should be stated. Further, the methods section mentions that Thin-mCherry was used for transfection and anti-DsRed antibody for detection on blots, but no corresponding results are described.

We are sorry about the shortcomings regarding the documentation of the biochemistry and cell culture experiments. Based on this concern, we repeated the Western blot analysis. Since it was difficult to detect mCherry-tagged Thin, we generated and expressed HA-tagged Thin (pUAS-HA-thin). However, it was also challenging to detect pUAS-HA-thin on Western blots (Figure 5—figure supplement 2C). This may be due to Thin’s large disordered domains and/or its comparably large size (Figure 1—figure supplement 2A). Quantification of the Thin/Tubulin ratio at 1x and 2x thin DNA concentration revealed an increase of Thin/Tubulin that correlated with HA-thin DNA concentration (not shown). However, the low signal-to-noise ratio of the Thin signal precludes a meaningful quantification and interpretation of these data. We thus plotted Dysbindin/Tubulin for cells transfected without, 1x and 2x pUAS-HA-thin (now specified in the Methods section). Note that we are confident about a robust thin transfection efficiency, because we consistently observed mCherry-positive cells in the old experiments, as well as anti-HA signal in the last rounds of Western blots.

We chose a new example that better reflects the average data (Figure 5— figure supplement 2C). Note that – besides the fact that most blots showed some ‘cosmetic flaws’ (Figure 5—figure supplement 2C); we explicitly show a representative instead of the best example – we consistently observed a reduction in anti-GFP/anti-Tubulin that correlated with pUAS-HA-thin concentration, thereby strongly supporting the idea that Thin degrades Dysbindin in Drosophila.

The new blot does not display faint bands at >60kDa. We also verified that the new blot is labelled correctly, including the correct molecular sizes.

The legend now specifies that pUAS-venus-Dysbindin (‘Dysbindinvenus’) and pUAS-HA-thin (‘ThinHA’) were detected with anti-GFP and anti-HA, respectively. The quantification of anti-GFP (Dysbindinvenus) was now normalized to anti-Tubulin (Figure 5—figure supplement 2D). The Methods section was updated correspondingly.

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

The manuscript has been improved very substantially. No further experiments are required, but there are five remaining issues that need to be addressed by changes to the manuscript, as outlined below:

1. The authors state in their rebuttal that "Under baseline conditions, i.e. in the absence of PhTX, the miniature amplitude was decreased in thinΔA mutants (Figure 2B), after presynaptic and postsynaptic rescue (Figure 2B)". However, in Figure 2B, the gray and light red bars show significant differences, while gray and light blue/light green bars do not. This indicates that mEPSC amplitudes were NOT decreased in thinΔA mutants upon presynaptic or postsynaptic rescue. Can this be clarified or is there an underlying asterisk labeling error? The latter, if relevant, might warrant a final detailed check of the entire manuscript.

mEPSC amplitudes were decreased after presynaptic rescue (p<0.001) and

postsynaptic rescue (p=0.04) in the thinΔA mutant background compared to WT. Hence, there was indeed an asterisk labeling error in Figure 2B. We are sorry about this mistake and thank the reviewers for catching it. We now updated Figure 2B correspondingly.

2. Demonstrating an increase in Dysbindin levels in thin mutants is important. Many reports have demonstrated reduced expression of alleged "substrates" upon overexpression of a corresponding E3 – as shown in Figure 5. Figure S2C. However, such results have limited value. Overexpression of an E3 can cause artificial ubiquitination by excess enzyme binding with low-affinity to proteins that are not endogenous substrates. Since it is not difficult to detect Dysbindin-Venus by Western blotting, the best experiment under the current circumstances might be to study thin mutant flys expressing low levels of Dysbindin-Venus. At this juncture, the reviewers do not require this experiment to be done. Instead, the authors should conservatively rephrase their conclusion that Dysbindin is regulated by the UPS in a Thin-dependent manner (Figure 6F) and might eliminate "26S" from Figure 6F and change the text accordingly.

We completely agree and rephrased our conclusions regarding Dysbindin regulation by the UPS throughout the text. We also directly address this point in the Results section:

"Although we cannot exclude the possibility that Thin overexpression induced artificial Dysbindin ubiquitination by excess enzyme binding with low affinity, these data are consistent with the idea that Thin acts as an E3 ligase for Dysbindin in Drosophila, similar to TRIM32 in humans (Locke et al., 2009)." (l. 330). Moreover, we eliminated the model shown in Figure 6F to avoid any confusion.

3. There appears to be a misunderstanding regarding the reviewers' comment C5 – the concerns regarding discrepancies between Figure 2C and Figure 4C. In the reviewers' view, the expression of thin should be the same in these two scenarios; no thin expression in presynapse but intact expression in postsynapse. There should not be any difference between the results in Figure 2C and Figure 4C. This issue should be explained and resolved.

We agree – in theory, postsynaptic thin rescue (Figure 2C) should produce a similar phenotype as presynaptic thin-RNAi expression (Figure 4C). Indeed, the increase in quantal content under baseline conditions is very similar between postsynaptic thin rescue (Figure 2E, light green bar) and presynaptic thin-RNAi expression (Figure 4D), in line with a model in which presynaptic thin perturbation increases quantal content in both genotypes. The smaller mEPSC and EPSC amplitudes under baseline conditions after postsynaptic thin rescue (Figure 2B, C) compared to thin-RNAi (Figure 4B, C) are most likely due to non-endogenous Thin levels caused by thin overexpression in the thinΔA mutant background. We now discuss this possibility in the main text: "Note that the smaller mEPSC and EPSC amplitudes under baseline conditions after postsynaptic thin rescue (Figure 2B, C) compared to thinRNAi (Figure 4B, C) are most likely due to non-endogenous postsynaptic Thin levels caused by thin overexpression in the thinΔA mutant background." (l. 256)

4. The identity of the transgenic lines shown in Figure 1E should be disclosed. The authors have done a good job of listing all genotypes. However, in its present form, the assignment of individual genotypes to data points on the volcano plot cannot be clearly extracted from the supplementary table. As a compromise, the authors could use the red colour code in the table as previously suggested (comment C1).

As suggested, we now labeled transgenic lines with significantly altered EPSC amplitude in red in the supplementary table and sorted the lines according to EPSC amplitude.

5. To avoid word repetition, the reviewers suggest slightly rephrasing the sentence "Regarding the decrease in Brp intensity, Brp intensity was decreased…" (lines 230-231).

We changed the text correspondingly: "Furthermore, Brp intensity was decreased after presynaptic rescue (…)." (l. 225).

https://doi.org/10.7554/eLife.71437.sa2

Article and author information

Author details

  1. Martin Baccino-Calace

    1. Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    2. Zurich Ph.D. Program in Molecular Life Sciences, Zurich, Switzerland
    Contribution
    Conceptualization, Software, Formal analysis, Investigation, Visualization, Writing – original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4143-4166
  2. Katharina Schmidt

    Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    Contribution
    Conceptualization, Formal analysis, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2797-9952
  3. Martin Müller

    1. Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    2. Zurich Ph.D. Program in Molecular Life Sciences, Zurich, Switzerland
    3. Neuroscience Center Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    For correspondence
    Martin.Mueller@mls.uzh.ch
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1624-6761

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PP00P3-15)

  • Martin Müller

European Research Council (SynDegrade-679881)

  • Martin Müller

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

Acknowledgements

We are grateful to the members of the Müller lab for helpful discussions and critical comments on the manuscript. We thank Dr. Damian Szklarczyk for help with STRING-based protein–protein interaction analysis used for prioritization of E3 ligases, and Dr. Marian Hruska-Plochan for help with the western blot analysis. Stocks obtained from the Bloomington Drosophila Stock Center (NIH P40OD018537) were used in this study.

Senior Editor

  1. Lu Chen, Stanford University, United States

Reviewing Editor

  1. Nils Brose, Max Planck Institute of Experimental Medicine, Germany

Reviewers

  1. Hiroshi Kawabe, Gunma University, Japan
  2. Eckart D Gundelfinger, Leibniz Institute for Neurobiology, Magdeburg, Germany, Germany

Publication history

  1. Preprint posted: June 16, 2021 (view preprint)
  2. Received: June 19, 2021
  3. Accepted: July 6, 2022
  4. Accepted Manuscript published: July 7, 2022 (version 1)
  5. Version of Record published: July 20, 2022 (version 2)

Copyright

© 2022, Baccino-Calace 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

  • 512
    Page views
  • 204
    Downloads
  • 0
    Citations

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

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. Martin Baccino-Calace
  2. Katharina Schmidt
  3. Martin Müller
(2022)
The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression
eLife 11:e71437.
https://doi.org/10.7554/eLife.71437

Further reading

    1. Developmental Biology
    2. Genetics and Genomics
    Suhee Chang, Diana Fulmer ... Marisa S Bartolomei
    Research Article

    Dysregulation of the imprinted H19/IGF2 locus can lead to Silver-Russell syndrome (SRS) in humans. However, the mechanism of how abnormal H19/IGF2 expression contributes to various SRS phenotypes remains unclear, largely due to incomplete understanding of the developmental functions of these two genes. We previously generated a mouse model with humanized H19/IGF2 imprinting control region (hIC1) on the paternal allele that exhibited H19/Igf2 dysregulation together with SRS-like growth restriction and perinatal lethality. Here, we dissect the role of H19 and Igf2 in cardiac and placental development utilizing multiple mouse models with varying levels of H19 and Igf2. We report severe cardiac defects such as ventricular septal defects and thinned myocardium, placental anomalies including thrombosis and vascular malformations, together with growth restriction in mouse embryos that correlated with the extent of H19/Igf2 dysregulation. Transcriptomic analysis using cardiac endothelial cells of these mouse models shows that H19/Igf2 dysregulation disrupts pathways related to extracellular matrix and proliferation of endothelial cells. Our work links the heart and placenta through regulation by H19 and Igf2, demonstrating that accurate dosage of both H19 and Igf2 is critical for normal embryonic development, especially related to the cardiac-placental axis.

    1. Evolutionary Biology
    2. Genetics and Genomics
    Yi Feng, Rafik Neme ... Laura F Landweber
    Research Article

    Ciliates are microbial eukaryotes that undergo extensive programmed genome rearrangement, a natural genome editing process that converts long germline chromosomes into smaller gene-rich somatic chromosomes. Three well-studied ciliates include Oxytricha trifallax, Tetrahymena thermophila and Paramecium tetraurelia, but only the Oxytricha lineage has a massively scrambled genome, whose assembly during development requires hundreds of thousands of precise programmed DNA joining events, representing the most complex genome dynamics of any known organism. Here we study the emergence of such complex genomes by examining the origin and evolution of discontinuous and scrambled genes in the Oxytricha lineage. This study compares six genomes from three species, the germline and somatic genomes for Euplotes woodruffi, Tetmemena sp., and the model ciliate Oxytricha trifallax. To complement existing data, we sequenced, assembled and annotated the germline and somatic genomes of Euplotes woodruffi, which provides an outgroup, and the germline genome of Tetmemena sp.. We find that the germline genome of Tetmemena is as massively scrambled and interrupted as Oxytricha's : 13.6% of its gene loci require programmed translocations and/or inversions, with some genes requiring hundreds of precise gene editing events during development. This study revealed that the earlier-diverged spirotrich, E. woodruffi, also has a scrambled genome, but only roughly half as many loci (7.3%) are scrambled. Furthermore, its scrambled genes are less complex, together supporting the position of Euplotes as a possible evolutionary intermediate in this lineage, in the process of accumulating complex evolutionary genome rearrangements, all of which require extensive repair to assemble functional coding regions. Comparative analysis also reveals that scrambled loci are often associated with local duplications, supporting a gradual model for the origin of complex, scrambled genomes via many small events of DNA duplication and decay.